Abstract: Smart Dust is comprised of a vast number of ultra-small fully autonomous computing and communication devices, with very restricted energy and computing capabilities, that co-operate to accomplish a large sensing task. Smart Dust can be very useful in practice i.e. in the local detection of a remote crucial event and the propagation of data reporting its realization to a control center.
In this work, we have implemented and experimentally evaluated four protocols (PFR, LTP and two variations of LTP which we here introduce) for local detection and propagation in smart dust networks, under new, more general and realistic modelling assumptions. We comparatively study, by using extensive experiments, their behavior highlighting their relative advantages and disadvantages. All protocols are very successful. In the setting we considered here, PFR seems to be faster while the LTP based protocols are more energy efficient.
Abstract: Smart Dust is comprised of a vast number of ultra-small fully autonomous computing and communication devices, with very restricted energy and computing capabilities, that co-operate to accomplish a large sensing task. Smart Dust can be very useful in practice i.e. in the local detection of a remote crucial event and the propagation of data reporting its realization to a control center.
In this work, we have implemented and experimentally evaluated four protocols (PFR, LTP and two variations of LTP which we here introduce) for local detection and propagation in smart dust networks, under new, more general and realistic modelling assumptions. We comparatively study, by using extensive experiments, their behavior highlighting their relative advantages and disadvantages. All protocols are very successful. In the setting we considered here, PFR seems to be faster while the LTP based protocols are more energy efficient.
Abstract: Large-scale sensor networks, monitoring an environment at close range with high spatial and temporal resolutions are expected to play an important role in various applications, e.g., assessing the ``health'' of machines; environmental, medical, food-safety, and habitat monitoring; inventory control, building automation, etc. Ensuring the security of these complex and yet resource-constrained systems has emerged as one of the most pressing challenges for researchers. In this paper (i) we present the major threats and some characteristic countermeasures, (ii) we propose a way to classify existing systems for intrusion detection in wireless sensor networks and (iii) we present a new approach for decentralized energy efficient intrusion detection that can be used to improve security from both external and internal adversaries.
Abstract: We here present the Forward Planning Situated Protocol (FPSP), for scalable, energy efficient and fault tolerant data propagation in situated wireless sensor networks. To deal with the increased complexity of such deeply networked sensor systems, instead of emphasizing on a particular aspect of the services provided, i.e. either for low-energy periodic, or low-latency event-driven, or high-success query-based sensing, FPSP uses two novel mechanisms that allow the network operator to adjust the performance of the protocol in terms of energy, latency and success rate on a per-task basis. We emphasize on distributedness, direct or indirect interactions among relatively simple agents, flexibility and robustness.
The protocol operates by employing a series of plan & forward phases through which devices self-organize into forwarding groups that propagate data over discovered paths. FPSP performs a limited number of long range, high power data transmissions to collect information regarding the neighboring devices. The acquired information, allows to plan a (parameterizable long by {\"e}) sequence of short range, low power transmissions between nearby particles, based on certain optimization criteria. All particles that decide to respond (based on local criteria) to these long range transmissions enter the forwarding phase during which information is propagated via the acquired plan. Clearly, the duration of the forwarding phases is characterized by the parameter {\"e}, the transmission medium and the processing speed of the devices. In fact the parameter {\"e} provides a mechanism to adjust the protocol performance in terms of the latency--energy trade-off. By reducing {\"e} the latency is reduced at the cost of spending extra energy, while by increasing {\"e}, the energy dissipation is reduced but the latency is increased.
To control the success rate--energy trade-off, particles react locally on environment and context changes by using a set of rules that are based on response thresholds that relate individual-level plasticity with network-level resiliency, motivated by the nature-inspired method for dividing labor, a metaphor of social insect behavior for solving problems [1]. Each particle has an individual response threshold {\`E} that is related to the "local" density (as observed by the particle, [2]); particles engage in propagation of events when the level of the task-associated stimuli exceeds their thresholds. Let s be the intensity of a stimulus associated with a particular sensing task, set by the human authorities. We adopt the response function T{\`e}(s) = snover sn + {\`e}n, the probability of performing the task as a function of s, where n > 1 determines the steepness of the threshold. Thus, when {\`e} is small (i.e. the network is sparse) then the response probability increases; when s increases (i.e. for critical sensing tasks) the response probability increases as well.
This role-based approach where a selective number of devices do the high cost planning and the rest of the network operates in a low cost state leads to systems that have increased energy efficiency and high fault-tolerance since these long range planning phases allow to bypass obstacles (where no sensors are available) or faulty sensors (that have been disabled due to power failure or other natural events).
Abstract: This work addresses networked embedded systems enabling the seam-
less interconnection of smart building automations to the Internet and
their abstractions as web services. In our approach, such abstractions are
used to primarily create a exible, holistic and scalable system and allow
external end-users to compose and run their own smart/green building
automation application services on top of this system.
Towards this direction, in this paper we present a smart building test-
bed consisting of several sensor motes and spanning across seven rooms.
Our test-bed's design and implementation simultaneously addresses sev-
eral corresponding system layers; from hardware interfaces, embedded
IPv6 networking and energy balancing routing algorithms to a RESTful
architecture and over the web development of sophisticated, smart, green
scenarios. In fact, we showcase how IPv6 embedded networking combined
with RESTful architectures make the creation of building automation ap-
plications as easy as creating any other Internet Web Service.
Abstract: With the proliferation of wireless sensor net-
works and mobile technologies in general, it is possible to
provide improved medical services and also to reduce costs
as well as to manage the shortage of specialized personnel.
Monitoring a person’s health condition using sensors pro-
vides a lot of benefits but also exposes personal sensitive
information to a number of privacy threats. By recording
user-related data, it is often feasible for a malicious or
negligent data provider to expose these data to an unau-
thorized user. One solution is to protect the patient’s pri-
vacy by making difficult a linkage between specific
measurements with a patient’s identity. In this paper we
present a privacy-preserving architecture which builds
upon the concept of
k
-anonymity; we present a clustering-
based anonymity scheme for effective network manage-
ment and data aggregation, which also protects user’s
privacy by making an entity indistinguishable from other
k
similar entities. The presented algorithm is resource
aware, as it minimizes energy consumption with respect to
other more costly, cryptography-based approaches. The
system is evaluated from an energy-consuming and net-
work performance perspective, under different simulation
scenarios.
Abstract: Motivated by the problem of supporting energy-efficient broadcasting in ad hoc wireless networks, we study the Minimum
Energy Consumption Broadcast Subgraph (MECBS) problem. We present the first logarithmic approximation algorithm for the
problem which uses an interesting reduction to Node-Weighted Connected Dominating Set.
Abstract: A considerable part of recent research in smart cities and IoT has focused on achieving energy savings in buildings and supporting aspects related to sustainability. In this context, the educational community is one of the most important ones to consider, since school buildings constitute a large part of non-residential buildings, while also educating students on sustainability matters is an investment for the future. In this work, we discuss a methodology for achieving energy savings in schools based on the utilization of data produced by an IoT infrastructure installed inside school buildings and related educational scenarios. We present the steps comprising this methodology in detail, along with a set of tangible results achieved within the GAIA project. We also showcase how an IoT infrastructure can support activities in an educational setting and produce concrete outcomes, with typical levels of 20% energy savings.
Abstract: Smart Dust is a special case of wireless sensor networks, comprised of a vast number of ultra-small fully autonomous computing, communication and sensing devices, with very restricted energy and computing capabilities, that co-operate to accomplish a large sensing task. Smart Dust can be very useful in practice, i.e. in the local detection of remote crucial events and the propagation of data reporting their realization to a control center.
In this paper, we propose a new energy efficient and fault tolerant protocol for data propagation in smart dust networks, the Variable Transmission Range Protocol (VTRP). The basic idea of data propagation in VTRP is the varying range of data transmissions, i.e. we allow the transmission range to increase in various ways. Thus, data propagation in our protocol exhibits high fault-tolerance (by bypassing obstacles or faulty sensors) and increases network lifetime (since critical sensors, i.e. close to the control center are not overused). As far as we know, it is the first time varying transmission range is used.
We implement the protocol and perform an extensive experimental evaluation and comparison to a representative protocol (LTP) of several important performance measures with a focus on energy consumption. Our findings indeed demonstrate that our protocol achieves significant improvements in energy efficiency and network lifetime.
Abstract: In this work we propose a new energy efficient and fault tolerant protocol for data propagation in wireless sensor networks, the Variable Transmission Range Protocol VTRP. The basic idea of data propagation in VTRP is the varying range of data transmissions, ie. we allow the transmission range to increase in various ways. Thus data propagation in our protocol exhibits high fault-tolerance (by bypassing obstacles or faulty sensors) and increases network lifetime (since critical sensors, ie. close to the control center are not overused). As far as we know, it is the first time varying transmission range is used.
We implement the protocol and perform an extensive experimental evaluation and comparison to a representative protocol (LTP) of several important performance measures with a focus on energy consumption. Our findings indeed demonstrate that our protocol achieves significant improvements in energy efficiency and network lifetime.
Abstract: We study the problem of data propagation in sensor networks,
comprised of a large number of very small and low-cost nodes,
capable of sensing, communicating and computing. The distributed
co-operation of such nodes may lead to the accomplishment of large
sensing tasks, having useful applications in practice. We present
a new protocol for data propagation towards a control center
(``sink") that avoids flooding by probabilistically favoring
certain (``close to optimal") data transmissions.
This protocol is very simple to implement in sensor devices
and operates under total absence
of co-ordination between sensors. We consider a network model of randomly deployed sensors of sufficient density.
As shown by a geometry analysis,
the protocol is correct, since it always propagates data
to the sink, under ideal network conditions (no failures). Using
stochastic processes, we show that the protocol is very energy efficient. Also, when part of the network is inoperative, the
protocol manages to propagate data very close to the sink, thus in
this sense it is robust. We finally present and discuss
large-scale experimental findings validating the analytical
results.
Abstract: We study the problem of data propagation in sensor networks,
comprised of a large number of very small and low-cost nodes,
capable of sensing, communicating and computing. The distributed
co-operation of such nodes may lead to the accomplishment of large
sensing tasks, having useful applications in practice. We present a new protocol for data propagation towards a control center ("sink") that avoids flooding by probabilistically favoring certain ("close to optimal") data transmissions. Motivated by certain applications and also as a starting point for a rigorous analysis, we study here lattice-shaped sensor networks. We however show that this lattice shape emerges even in randomly deployed sensor networks of sufficient sensor density. Our work is inspired and builds upon the directed diffusion paradigm.
This protocol is very simple to implement in sensor devices, uses only local information and operates under total absence of co-ordination between sensors. We consider a network model of randomly deployed sensors of sufficient density. As shown by a geometry analysis, the protocol is correct, since it always propagates data to the sink, under ideal network conditions (no failures). Using stochastic processes, we show that the protocol is very energy efficient. Also, when part of the network is inoperative, the protocol manages to propagate data very close to the sink, thus in this sense it is robust. We finally present and discuss large-scale experimental findings validating the analytical results.
Abstract: Raising awareness among young people on the
relevance of behaviour change for achieving energy savings is widely considered as a key approach towards long-term and costeffective energy efficiency policies. The GAIA Project aims to deliver a comprehensive solution for both increasing awareness on energy efficiency and achieving energy savings in school buildings. In this framework, we present a novel rule engine that, leveraging a resource-based graph model encoding relevant application domain knowledge, accesses IoT data for producing energy savings recommendations. The engine supports configurability, extensibility and ease-of-use requirements, to be easily applied and customized to different buildings. The paper introduces the main design and implementation details and presents a set of preliminary performance results.
Abstract: Smart Dust is a set of a vast number of ultra-small fully
autonomous computing and communication devices, with very
restricted energy and computing capabilities, that co-operate to
quickly and efficiently accomplish a large sensing task. Smart
Dust can be very useful in practice i.e. in the local detection of
a remote crucial event and the propagation of data reporting its
realization. In this work we continue (see [POMC02]) our
effort towards the research on smart dust from a basic algorithmic
point of view. Under a simple but realistic model for smart dust
we present an interesting problem, which is how to propagate
efficiently information on an event detected locally. Then we
present a new smart dust protocol, which we call the
``Sleep-Awake" protocol, for information propagation that explicitly uses the energy saving features (i.e. the alteration of sleeping and awake time periods) of the smart dust particles. By using both probabilistic some first analysis and extensive
experiments, we provide some first concrete results for the
success probability and the time and energy efficiency of the
protocol, in terms of parameters of the smart dust network. We
note that the study of the interplay of these parameters allows us
to program the smart dust network characteristics accordingly.
Abstract: We propose a MAC protocol for mobile ad hoc networks that
uses power control for the RTS/CTS and DATA frame
transmissions in order to improve energy and capacity
utilization efficiency. Unlike IEEE 802.11, in our scheme the
RTS frames are not sent using the maximum transmission
power to silence neighbouring nodes, and the CTS frames do
not silence all receiving nodes to the same degree. In contrast,
the transmission power of the RTS frames follows a slow
start principle, while the CTS frames, which are sent at
maximum transmission power, prevent the neighbouring
nodes from transmitting their DATA frames with power more
than a computed threshold, while allowing them to transmit at
power levels less than that threshold. This is done by
including in the RTS and the CTS frames additional
information, such as the power of the transmissions, and the
interference tolerance of the nodes. Moreover the DATA
frames are sent at the minimum required transmission power
increased by a small margin to ensure connectivity with the
intended receiver, so as to cause minimal interference to
neighbouring nodes and allow for future interference to be
added to the receiver of the DATA frames. The power to be
used by the transmitter is computed by the recipient of the
RTS frame and is included in the CTS frame. It is expected
that a network with such a power management scheme would
achieve a better throughput performance and more power
savings than a network without such a scheme.
Abstract: We propose a MAC protocol for mobile ad hoc networks that
uses power control for the RTS/CTS and DATA frame
transmissions in order to improve energy and capacity
utilization efficiency. Unlike IEEE 802.11, in our scheme the
RTS frames are not sent using the maximum transmission
power to silence neighbouring nodes, and the CTS frames do
not silence all receiving nodes to the same degree. In contrast,
the transmission power of the RTS frames follows a slow
start principle, while the CTS frames, which are sent at
maximum transmission power, prevent the neighbouring
nodes from transmitting their DATA frames with power more
than a computed threshold, while allowing them to transmit at
power levels less than that threshold. This is done by
including in the RTS and the CTS frames additional
information, such as the power of the transmissions, and the
interference tolerance of the nodes. Moreover the DATA
frames are sent at the minimum required transmission power
increased by a small margin to ensure connectivity with the
intended receiver, so as to cause minimal interference to
neighbouring nodes and allow for future interference to be
added to the receiver of the DATA frames. The power to be
used by the transmitter is computed by the recipient of the
RTS frame and is included in the CTS frame. It is expected
that a network with such a power management scheme would
achieve a better throughput performance and more power
savings than a network without such a scheme.
Abstract: Designing wireless sensor networks is inherently complex; many aspects such as energy efficiency, limited resources, decentralized collaboration, fault tolerance have to be tackled. To be effective and to produce applicable results, fundamental research has to be tested, at least as a proof-of-concept, in large scale environments, so as to assess the feasibility of the new concepts, verify their large scale effects (not only at technological level, but also as for their foreseeable implications on users, society and economy) and derive further requirements, orientations and inputs for the research. In this paper we focus on the problems of interconnecting existing testbed environments via the Internet and providing a virtual unifying laboratory that will support academia, research centers and industry in their research on networks and services. In such a facility important issues of trust, security, confidentiality and integrity of data may arise especially for commercial (or not) organizations. In this paper we investigate such issues and present the design of a secure and robust architectural model for interconnecting testbeds of wireless sensor networks.
Abstract: We study the problem of fast and energy-efficient data collection of sensory data using a mobile sink, in wireless sensor networks in which both the sensors and the sink move. Motivated by relevant applications, we focus on dynamic sensory mobility and heterogeneous sensor placement. Our approach basically suggests to exploit the sensor motion to adaptively propagate information based on local conditions (such as high placement concentrations), so that the sink gradually “learns” the network and accordingly optimizes its motion. Compared to relevant solutions in the state of the art (such as the blind random walk, biased walks, and even optimized deterministic sink mobility), our method significantly reduces latency (the improvement ranges from 40% for uniform placements, to 800% for heterogeneous ones), while also improving the success rate and keeping the energy dissipation at very satisfactory levels.
Abstract: Motivated by emerging applications, we consider sensor networks where the sensors themselves (not just the sinks) are mobile. Furthermore, we focus on mobility scenarios characterized by heterogeneous, highly changing mobility roles in the network. To capture these high dynamics of diverse sensory motion we propose a novel network parameter,
the mobility level, which, although simple and local, quite accurately takes into account both the spatial and speed characteristics of motion. We then propose adaptive data dissemination protocols that use the mobility level estimation to optimize performance, by basically exploiting high mobility (redundant message ferrying) as a cost-effective replacement of flooding, e.g. the sensors tend to dynamically propagate less data in the presence
of high mobility, while nodes of high mobility are favored for moving data around. These dissemination schemes are enhanced by a distance-sensitive probabilistic message flooding inhibition mechanism that further reduces communication cost, especially for fast nodes of high mobility level, and as distance to data destination decreases. Our simulation findings
demonstrate significant performance gains of our protocols compared to non-adaptive protocols, i.e. adaptation increases the success rate and reduces latency (even by 15%) while at the same time significantly reducing energy dissipation (in most cases by even 40%). Also, our adaptive schemes achieve significantly higher message delivery ratio and
satisfactory energy-latency trade-offs when compared to flooding when sensor nodes have
limited message queues.
Abstract: We introduce a new modelling assumption for wireless sensor networks, that of node redeployment (addition of sensor devices during protocol evolution) and we extend the modelling assumption of heterogeneity (having sensor devices of various types). These two features further increase the highly dynamic nature of such networks and adaptation becomes a powerful technique for protocol design. Under these modelling assumptions, we design, implement and evaluate a new power conservation scheme for efficient data propagation. Our scheme is adaptive: it locally monitors the network conditions (density, energy) and accordingly adjusts the sleep-awake schedules of the nodes towards improved operation choices. The scheme is simple, distributed and does not require exchange of control messages between nodes.
Implementing our protocol in software we combine it with two well-known data propagation protocols and evaluate the achieved performance through a detailed simulation study using our extended version of the network simulator ns-2. We focus on highly dynamic scenarios with respect to network density, traffic conditions and sensor node resources. We propose a new general and parameterized metric capturing the trade-offs between delivery rate, energy efficiency and latency. The simulation findings demonstrate significant gains (such as more than doubling the success rate of the well-known Directed Diffusion propagation protocol) and good trade-offs achieved. Furthermore, the redeployment of additional sensors during network evolution and/or the heterogeneous deployment of sensors, drastically improve (when compared to ``equal total power" simultaneous deployment of identical sensors at the start) the protocol performance (i.e. the success rate increases up to four times} while reducing energy dissipation and, interestingly, keeping latency low).
Abstract: Clustering is a crucial network design approach to enable large-scale wireless sensor networks (WSNs) deployments. A large variety of clustering approaches has been presented focusing on different performance metrics. Such protocols usually aim at minimizing communication overhead, evenly distributing roles among the participating nodes, as well as controlling the network topology. Simulations on such protocols are performed using theoretical models that are based on unrealistic assumptions like the unit disk graph communication model, ideal wireless communication channels and perfect energy consumption estimations. With these assumptions taken for granted, theoretical models claim various performance milestones that cannot be achieved in realistic conditions. In this paper, we design a new clustering protocol that adapts to the changes in the environment and the needs and goals of the user applications. We address the issues that hinder its performance due to the real environment conditions and provide a deployable protocol. The implementation, integration and experimentation of this new protocol and it's optimizations, were performed using the \textsf{WISEBED} framework. We apply our protocol in multiple indoors wireless sensor testbeds with multiple experimental scenarios to showcase scalability and trade-offs between network properties and configurable protocol parameters. By analysis of the real world experimental output, we present results that depict a more realistic view of the clustering problem, regarding adapting to environmental conditions and the quality of topology control. Our study clearly demonstrates the applicability of our approach and the benefits it offers to both research \& development communities.
Abstract: Motivated by emerging applications, we consider sensor networks where the sensors themselves
(not just the sinks) are mobile. Furthermore, we focus on mobility
scenarios characterized by heterogeneous, highly changing mobility
roles in the network.
To capture these high dynamics of diverse sensory motion
we propose a novel network parameter, the mobility level, which, although
simple and local, quite accurately takes into account both the
spatial and speed characteristics of motion. We then propose
adaptive data dissemination protocols that use the
mobility level estimation to optimize performance, by basically
exploiting high mobility (redundant message ferrying) as a cost-effective
replacement of flooding, e.g., the sensors tend to dynamically propagate
less data in the presence of high mobility, while nodes of high mobility
are favored for moving data around.
These dissemination schemes are enhanced by a distance-sensitive
probabilistic message flooding inhibition mechanism that
further reduces communication cost, especially for fast nodes
of high mobility level, and as distance to data destination
decreases. Our simulation findings demonstrate significant
performance gains of our protocols compared to non-adaptive
protocols, i.e., adaptation increases the success rate and reduces
latency (even by 15\%) while at the same time significantly
reducing energy dissipation (in most cases by even 40\%).
Also, our adaptive schemes achieve significantly
higher message delivery ratio and satisfactory energy-latency
trade-offs when compared to flooding when sensor nodes have limited message queues.
Abstract: Motivated by emerging applications, we consider sensor networks where the sensors themselves
(not just the sinks) are mobile. We focus on mobility
scenarios characterized by heterogeneous, highly changing mobility
roles in the network.
To capture these high dynamics
we propose a novel network parameter, the mobility level, which, although
simple and local, quite accurately takes into account both the
spatial and speed characteristics of motion. We then propose
adaptive data dissemination protocols that use the
mobility level estimation to improve performance. By basically
exploiting high mobility (redundant message ferrying) as a cost-effective
replacement of flooding, e.g., the sensors tend to dynamically propagate
less data in the presence of high mobility, while nodes of high mobility
are favored for moving data around.
These dissemination schemes are enhanced by a distance-sensitive
probabilistic message flooding inhibition mechanism that
further reduces communication cost, especially for fast nodes
of high mobility level, and as distance to data destination
decreases. Our simulation findings demonstrate significant
performance gains of our protocols compared to non-adaptive
protocols, i.e., adaptation increases the success rate and reduces
latency (even by 15\%) while at the same time significantly
reducing energy dissipation (in most cases by even 40\%).
Also, our adaptive schemes achieve significantly
higher message delivery ratio and satisfactory energy-latency
trade-offs when compared to flooding when sensor nodes have limited message queues.
Abstract: Data propagation in wireless sensor networks can be performed either by hop-by-hop single transmissions or by multi-path broadcast of data. Although several energy-aware MAC layer protocols exist that operate very well in the case of single point-to-point transmissions, none is especially designed and suitable for multiple broadcast transmissions. The key idea of our protocols is the passive monitoring of local network conditions and the adaptation of the protocol operation accordingly. The main contribution of our adaptive method is to proactively avoid collisions by implicitly and early enough sensing the need for collision avoidance. Using the above ideas, we design, implement and evaluate three different, new strategies for proactive adaptation. We show, through a detailed and extended simulation evaluation, that our parameter-based family of protocols for multi-path data propagation significantly reduce the number of collisions and thus increase the rate of successful message delivery (to above 90%) by achieving satisfactory trade-offs with the average propagation delay. At the same time, our protocols are shown to be very energy efficient, in terms of the average energy dissipation per delivered message.
Abstract: We consider sensor networks where the sensor nodes are attached on entities that move in a highly dynamic, heterogeneous manner. To capture this mobility diversity we introduce a new network parameter, the direction-aware mobility
level, which measures how fast and close each mobile node is expected to get to the data destination (the sink). We then provide local, distributed data dissemination protocols
that adaptively exploit the node mobility to improve performance. In particular, "high" mobility is used as a low cost replacement for data dissemination (due to the ferrying of data), while in the case of "low" mobility either a) data propagation redundancy is increased (when highly mobile neighbors exist) or b) long-distance data transmissions are used (when the entire neighborhood is of low mobility) to accelerate data dissemination towards the sink. An extensive performance comparison to relevant methods from
the state of the art demonstrates signi cant improvements i.e. latency is reduced by even 4 times while keeping energy dissipation and delivery success at very satisfactory levels.
Abstract: We investigate the problem of ecient wireless energy recharging in Wireless Rechargeable Sensor Networks (WRSNs). In
such networks a special mobile entity (called the Mobile Charger) traverses the network and wirelessly replenishes the energy
of sensor nodes. In contrast to most current approaches, we envision methods that are distributed, adaptive and use limited
network information. We propose three new, alternative protocols for ecient recharging, addressing key issues which we
identify, most notably (i) to what extent each sensor should be recharged (ii) what is the best split of the total energy between
the charger and the sensors and (iii) what are good trajectories the MC should follow. One of our protocols (
LRP
) performs
some distributed, limited sampling of the network status, while another one (
RTP
) reactively adapts to energy shortage alerts
judiciously spread in the network. As detailed simulations demonstrate, both protocols signi cantly outperform known state
of the art methods, while their performance gets quite close to the performance of the global knowledge method (
GKP
) we
also provide, especially in heterogeneous network deployments.
Abstract: Energy consumption reserves a large portion of the budget for school buildings. At the same time, the students that use such facilities are the adults of the years to come and thus, should they embrace energy-aware behaviors, then sustainable results with respect to energy efficiency are anticipated. GAIA is a research project targeting this user domain, proposing a set of applications that a) aims at raising awareness, prompting action and fostering engagement in energy efficiency enhancement, and b) is adaptable to the needs of each facility/community. This application set relies on an IoT sensing infrastructure, as well as on the use of humans as sensors to create situational awareness.
Abstract: Wireless sensor networks are comprised of a vast number of
ultra-small autonomous computing, communication and sensing devices,
with restricted energy and computing capabilities, that co-operate
to accomplish a large sensing task. Such networks can be very useful
in practice, e.g.~in the local monitoring of ambient conditions and
reporting them to a control center. In this paper we propose a
distributed group key establishment protocol that uses mobile agents
(software) and is particularly suitable for energy constrained,
dynamically evolving ad-hoc networks. Our approach totally avoids
the construction and the maintenance of a distributed structure that
reflects the topology of the network. Moreover, it trades-off
complex message exchanges by performing some amount of additional
local computations in order to be applicable at dense and dynamic
sensor networks. The extra computations are simple for the devices
to implement and are evenly distributed across the participants of
the network leading to good energy balance. We evaluate the
performance of our protocol in a simulated environment and compare
our results with existing group key establishment protocols. The
security of the protocol is based on the Diffie-Hellman problem and
we used in our experiments its elliptic curve analog. Our findings
basically indicate the feasibility of implementing our protocol in
real sensor network devices and highlight the advantages and
disadvantages of each approach given the available technology and
the corresponding efficiency (energy, time) criteria.
Abstract: In this paper, we consider the problem of energy balanced data propagation in wireless sensor networks and we generalise previous works by allowing realistic energy assignment. A new modelisation of the process of energy consumption as a random walk along with a new analysis are proposed. Two new algorithms are presented and analysed. The first one is easy to implement and fast to execute. However, it needs a priori assumptions on the process generating data to be propagated. The second algorithm overcomes this need by inferring information from the observation of the process. Furthermore, this algorithm is based on stochastic estimation methods and is adaptive to environmental changes. This represents an important contribution for propagating energy balanced data in wireless sensor netwoks due to their highly dynamic nature.
Abstract: We introduce a new modelling assumption in wireless sensor networks, that of node redeployment (addition of sensor devices during the protocol evolution) and we extend the modelling assumption of heterogeneity (having sensor devices of various types). These two features further increase the highly dynamic nature of such networks and adaptation becomes a powerful technique for protocol design. Under this model, we design, implement and evaluate a power conservation scheme for efficient data propagation. Our protocol is adaptive: it locally monitors the network conditions (density, energy) and accordingly adjusts the sleep-awake schedules of the nodes towards best operation choices. Our protocol operates does not require exchange of control messages between nodes to coordinate.Implementing our protocol we combine it with two well-known data propagation protocols and evaluate the achieved performance through a detailed simulation study using our extended version of Ns2. We focus in highly dynamic scenarios with respect to network density, traffic conditions and sensor node resources. We propose a new general and parameterized metric capturing the trade-off between delivery rate, energy efficiency and latency. The simulation findings demonstrate significant gains (such as more than doubling the success rate of the well-known Directed Diffusion propagation paradigm) and good trade-offs. Furthermore, redeployment of sensors during network evolution and/or heterogeneous deployment of sensors drastically improve (when compared to equal total "power" simultaneous deployment of identical sensors at the start) the protocol performance (the success rate increases up to four times while reducing energy dissipation and, interestingly, keeping latency low).
Abstract: In this paper, a novel configuration is proposed for
the implementation of an almost all-optical switch architecture
called the scheduling switch, which when combined with appropriate
wait-for-reservation or tell-and-go connection and flow
control protocols provides lossless communication for traffic
that satisfies certain smoothness properties. An all-optical 2 2
exchange/bypass (E/B) switch based on the nonlinear operation
of a semiconductor optical amplifier (SOA) is considered as the
basic building block of the scheduling switch as opposed to active
SOA-based space switches that use injection current to switch
between ON and OFF states. The experimental demonstration of
the optically addressable 2 2 E/B, which is summarized for
10–Gb/s data packets as well as synchronous digital hierarchy
(SDH)/STM-64 data frames, ensures the feasibility of the proposed
configuration at high speeds, with low switching energy and low
losses during the scheduling process. In addition, it provides
reduction of the number of required components for the construction
of the scheduling switch, which is calculated to be 50% in the
number of active elements and 33% in the fiber length.
Abstract: The use of Augmented Reality (AR) technologies is currently being investigated in numerous and diverse application domains. In this work, we discuss the ways in which we are integrating AR into educational in-class activities for the GAIA project, aiming to enhance existing tools that target behavioral changes towards energy efficiency in schools. We combine real-time IoT data from a sensing infrastructure inside a fleet of school buildings with AR software running on tablets and smartphones, as companions to a set of educational lab activities aimed at promoting energy awareness in a STEM context. We also utilize this software as a means to ease access to IoT data and simplify device maintenance. We report on the design and current status of our implementation, describing functionality in the context of our target applications, while also relaying our experiences from the use of such technologies in this application domain.
Abstract: The use of maker community tools and IoT technologies inside classrooms is spreading to an ever-increasing number of education and science fields. GAIA is a European research project focused on achieving behavior change for sustainability and energy awareness in schools. In this work, we report on how a large IoT deployment in a number of educational buildings and real-world data from this infrastructure, are utilized to support a “maker” lab kit activity inside the classroom. We also provide some insights to the integration of these activities in the school curriculum, along with a discussion on feedback produced through a series of workshop activities in a number of schools in Greece. Moreover, we discuss the application of the lab kit framework towards implementing an interactive installation. We also report on how the lab kit is paired with a serious game and an augmented reality app for smartphones and tablets, supporting the in-class activities. Our initial evaluation results show a very positive first reaction by the school community.
Abstract: Wireless Sensor Networks are complex systems consisting of a number of relatively simple autonomous sensing devices spread on a geographical area. The peculiarity of these devices lies on the constraints they face in relation to their energy reserves and their computational, storage and communication capabilities. The utility of these sensors is to measure certain environmental conditions and to detect critical events in relation to these measurements. Those events thereupon have to be reported to a specific central station namely the “sink”. This data propagation generally has the form of a hop-by-hop transmission. In this framework we work on distributed data propagation protocols which are taking into account the energy reserves of the sensors. In particular following the work of Chatzigiannakis et al. on the Probabilistic Forwarding Protocol (PFR) we present the distributed probabilistic protocol EFPFR, which favors transmission from the less depleted sensors in addition to favor transmissions close to the “optimal line”. This protocol is simple and relies only on local information for propagation decisions. Its main goal is to limit the total amount of energy dissipated per event and therefore to extend the network’s operation duration.
Abstract: In this paper we present a new approximation algorithm for
the Minimum Energy Broadcast Routing (MEBR) problem in ad hoc
wireless networks that has exponentially better approximation factor
than the well-known Minimum Spanning Tree (MST) heuristic. Namely,
for any instance where a minimum spanning tree of the set of stations
is guaranteed to cost at most ˝ times the cost of an optimal solution
for MEBR, we prove that our algorithm achieves an approximation ra-
tio bounded by 2 ln ˝ ˇ 2 ln 2 + 2. This result is particularly relevant for
its consequences on Euclidean instances where we signiŻcantly improve
previous results.
Abstract: Raising awareness among young people and changing their behaviour and habits concerning energy usage is key to achieving sustained energy saving. Additionally, young people are very sensitive to environmental protection so raising awareness among children is much easier than with any other group of citizens. This work examines ways to create an innovative Information & Communication Technologies (ICT) ecosystem (including web-based, mobile, social and sensing elements) tailored specifically for school environments, taking into account both the users (faculty, staff, students, parents) and school buildings, thus motivating and supporting young citizens˘ behavioural change to achieve greater energy efficiency. A mixture of open-source IoT hardware and proprietary platforms on the infrastructure level, are currently being utilized for monitoring a fleet of 18 educational buildings across 3 countries, comprising over 700 IoT monitoring points. Hereon presented is the system˘s high-level architecture, as well as several aspects of its implementation, related to the application domain of educational building monitoring and energy efficiency. The system is developed based on open-source technologies and services in order to make it capable of providing open IT-infrastructure and support from different commercial hardware/sensor vendors as well as open-source solutions. The system presented can be used to develop and offer new app-based solutions that can be used either for educational purposes or for managing the energy efficiency of the building. The system is replicable and adaptable to settings that may be different than the scenarios envisioned here (e.g., targeting different climate zones), different IT infrastructures and can be easily extended to accommodate integration with other systems. The overall performance of the system is evaluated in real-world environment in terms of scalability, responsiveness and simplicity.
Abstract: We study the problem of greedy, single path data propaga-
tion in wireless sensor networks, aiming mainly to minimize
the energy dissipation. In particular, we rst mathemat-
ically analyze and experimentally evaluate the energy e-
ciency and latency of three characteristic protocols, each one
selecting the next hop node with respect to a di erent cri-
terion (minimum projection, minimum angle and minimum
distance to the destination). Our analytic and simulation
ndings suggest that any single criterion does not simulta-
neously satisfy both energy eciency and low latency. To-
wards parameterized energy-latency trade-o s we provide as
well hybrid combinations of the two criteria (direction and
proximity to the sink). Our hybrid protocols achieve sig-
ni cant perfomance gains and allow ne-tuning of desired
performance. Also, they have nice energy balance proper-
ties, and can prolong the network lifetime.
Abstract: In this paper we address the problem of estimating the num-
ber of stations in a wireless network. Under the assumption that each
station can detect collisions, we show that it is possible to estimate the
number stations in the network within a factor 2 from the correct value
in time O(log n log log n). We further show that if no station can detect
collisions, the same task can be accomplished within a factor of 3 in time
O(log2 n) and maximum energy O(log n) per node, with high probability.
Finally, we present an algorithm that computes the minimum value held
by the stations in the wireless network in time O(log2 n).
Abstract: Collecting sensory data using a mobile data sink has
been shown to drastically reduce energy consumption at the cost of increasing delivery delay. Towards improved energy-latency trade-offs, we propose a biased, adaptive sink mobility scheme, that adjusts to local network conditions, such as the surrounding density, remaining energy and the number of past visits in each network region. The sink moves probabilistically, favoring less visited areas in order to cover the network area faster, while adaptively stopping more time in network regions that tend to produce more data. We implement and evaluate our mobility scheme via simulation in diverse network settings. Compared to known blind random, non-adaptive schemes, our method achieves
significantly reduced latency, especially in networks with nonuniform sensor distribution, without compromising the energy efficiency and delivery success.
Abstract: Collecting sensory data using a mobile data sink has been shown to drastically reduce energy consumption at the cost of increasing delivery delay. Towards improved energy-latency trade-offs, we propose a biased, adaptive sink mobility scheme, that adjusts to local network conditions, such as the surrounding density, remaining energy and the number of past visits in each network region. The sink moves probabilistically, favoring less visited areas in order to cover the network area faster, while adaptively stopping more time in network regions that tend to produce more data. We implement and evaluate our mobility scheme via simulation in diverse network settings. Compared to known blind random, non-adaptive schemes, our method achieves significantly reduced latency, especially in networks with nonuniform sensor distribution, without compromising the energy efficiency and delivery success.
Abstract: Collecting sensory data using a mobile data sink has
been shown to drastically reduce energy consumption at the cost of increasing delivery delay. Towards improved energy-latency trade-offs, we propose a biased, adaptive sink mobility scheme, that adjusts to local network conditions, such as the surrounding
density, remaining energy and the number of past visits in each network region. The sink moves probabilistically, favoring less visited areas in order to cover the network area faster, while adaptively stopping more time in network regions that tend to
produce more data. We implement and evaluate our mobility scheme via simulation in diverse network settings. Compared to known blind random, non-adaptive schemes, our method achieves
significantly reduced latency, especially in networks with nonuniform sensor distribution, without compromising the energy efficiency and delivery success.
Abstract: We study the problem of energy-balanced data propagation in wireless sensor networks. The energy balance property is crucial for maximizing the time the network is functional, by avoiding early energy depletion of a large portion of sensors. We propose a distributed, adaptive data propagation algorithm that exploits limited, local network density information for achieving energy-balance while at the same time
minimizing energy dissipation.
We investigate both uniform and heterogeneous sensor placement distributions. By a detailed experimental evaluation and comparison with well-known energy-balanced protocols, we show that our density-based protocol improves energy efficiency signi cantly while also having better energy balance properties.
Furthermore, we compare the performance of our protocol with a centralized, o -line optimum solution derived by a linear program which maximizes the network lifetime and show that it achieves near-optimal performance for uniform sensor deployments.
Abstract: This chapter aims at presenting certain important aspects of the design of lightweight, event-driven algorithmic solutions for data dissemination in wireless sensor networks that provide support for reliable, efficient and concurrency-intensive operation. We wish to emphasize that efficient solutions at several levels are needed, e.g.~higher level energy efficient routing protools and lower level power management schemes. Furthermore, it is important to combine such different level methods into integrated protocols and approaches. Such solutions must be simple, distributed and local. Two useful algorithmic design principles are randomization (to trade-off efficiency and fault-tolerance) and adaptation (to adjust to high network dynamics towards improved operation). In particular, we provide a) a brief description of the technical specifications of state-of-the-art sensor devices b) a discussion of possible models used to abstract such networks, emphasizing heterogeneity, c) some representative power management schemes, and d) a presentation of some characteristic protocols for data propagation. Crucial efficiency properties of these schemes and protocols (and their combinations, in some cases) are investigated by both rigorous analysis and performance evaluations through large scale simulations.
Abstract: This paper addresses the problem of counting the size of a network where (i) processes have the same identifiers (anonymous nodes) and (ii) the et-
work topology constantly changes (dynamic network). Changes are riven by a powerful adversary that can look at internal process states and add and remove edges in order to contrast the convergence of the algorithm to the correct count. The paper proposes two leader-based counting algorithms. Such algorithms are based on a technique that mimics an energy-transfer between network nodes. The first algorithm assumes that the adversary cannot generate either disconnected network graphs or network graphs where nodes have degree greater than D. In such algorithm, the leader can count the size of the network and detect the counting termination in a finite time (i.e., conscious counting algorithm). The second algorithm assumes that the adversary only keeps the network graph connected at any time and we prove that the leader can still converge to a correct count in a finite number of rounds, but it is not conscious when this convergence happens.
Abstract: We consider a synchronous distributed system with n processes that communicate through a dynamic network guaranteeing 1-interval connectivity i.e., the network topology graph might change at each interval while keeping the graph connected at any time. The processes belonging to the distributed system are identified through a set of labels L = {l1 , l2 . . . , lk } (with 1 ≤ k < n). In this challenging system model, the paper addresses the following problem: ”counting the number of processes with the same label”. We provide a distributed algorithm that is able solve the problem based on the notion of energy transfer. Each process owns a fixed energy charge, and tries to discharge itself exchanging, at each round, at most half of its charge with neighbors. The paper also discusses when such counting is possible in the presence of failures. Counting processes with the same label in dynamic networks with homonyms is of great importance because it is as difficult as computing generic aggregating functions.
Abstract: Random walks in wireless sensor networks can serve as fully
local, very simple strategies for sink motion that reduce energy dissipa-
tion a lot but increase the latency of data collection. To achieve satis-
factory energy-latency trade-offs the sink walks can be made adaptive,
depending on network parameters such as density and/or history of past
visits in each network region; but this increases the memory require-
ments. Towards better balances of memory/performance, we propose two
new random walks: the Random Walk with Inertia and the Explore-and-
Go Random Walk; we also introduce a new metric (Proximity Varia-
tion) that captures the different way each walk gets close to the network
nodes. We implement the new walks and experimentally compare them
to known ones. The simulation findings demonstrate that the new walk˘s
performance (cover time) gets close to the one of the (much stronger)
biased walk, while in some other respects (partial cover time, proximity
variation) they even outperform it. We note that the proposed walks
have been fine-tuned in the light of experimental findings.
Abstract: In this work, we develop an IPv6 enabled smart building test-bed facility, by combining sensing and communication devices and functionalities. We address the Internet of Things paradigm by using diverse heterogeneous devices such as smartphones, sensor motes, NFC technology and traditional electrical devices, each one serving a specific role in the test-bed facility. Also, we extend a basic actuation component by making it self-aware, in terms of supported resources. Those enhancements allow us to enrich the test-bed’s capabilities in terms of M2M communication, portability and decentralization of the actuation process. Finally, we provide a simple smart room scenario for a tunable combination of energy eciency and comfort, which automatically adjusts the room’s light level based on ambient conditions and user preferences and demonstrate the feasibility of our system.
Abstract: We have designed and implemented a platform that enables monitoring and actuation in multiple buildings, that has been utilised in the context of a research project in Greece, focusing on public school buildings. The Green Mindset project has installed IoT devices in 12 Greek public schools to monitor energy consumption, along with indoor and outdoor environmental parameters. We present the architecture and actual deployment of our system, along with a first set of findings.
Abstract: Wireless sensor networks are comprised of a vast number of ultra-small autonomous computing, communication and sensing devices, with restricted energy and computing capabilities, that co-operate to accomplish a large sensing task. Such networks can be very useful in practice, e.g.~in the local monitoring of ambient conditions and reporting them to a control center. In this paper we propose a new lightweight, distributed group key establishment protocol suitable for such energy constrained networks. Our approach basically trade-offs complex message exchanges by performing some amount of additional local computations. The extra computations are simple for the devices to implement and are evenly distributed across the participants of the network leading to good energy balance. We evaluate the performance our protocol in comparison to existing group key establishment protocols both in simulated and real environments. The intractability of all protocols is based on the Diffie-Hellman problem and we used its elliptic curve analog in our experiments. Our findings basically indicate the feasibility of implementing our protocol in real sensor network devices and highlight the advantages and disadvantages of each approach given the available technology and the corresponding efficiency (energy, time) criteria.
Abstract: Wireless sensor networks are comprised of a vast number of ultra-small autonomous computing, communication and sensing devices, with restricted energy and computing capabilities, that co-operate to accomplish a large sensing task. Such networks can be very useful in practice, e.g.~in the local monitoring of ambient conditions and reporting them to a control center. In this paper we propose a new lightweight, distributed group key establishment protocol suitable for such energy constrained networks. Our approach basically trade-offs complex message exchanges by performing some amount of additional local computations. The extra computations are simple for the devices to implement and are evenly distributed across the participants of the network leading to good energy balance. We evaluate the performance our protocol in comparison to existing group key establishment protocols both in simulated and real environments. The intractability of all protocols is based on the Diffie-Hellman problem and we used its elliptic curve analog in our experiments. Our findings basically indicate the feasibility of implementing our protocol in real sensor network devices and highlight the advantages and disadvantages of each approach given the available technology and the corresponding efficiency (energy, time) criteria.
Abstract: Wireless Sensor Networks consist of a large number of small, autonomous devices, that are able to interact with their inveronment by sensing and collaborate to fulfill their tasks, as, usually, a single node is incapable of doing so; and they use wireless communication to enable this collaboration. Each device has limited computational and energy resources, thus a basic issue in the applicastions of wireless sensor networks is the low energy consumption and hence, the maximization of the network lifetime.
The collected data is disseminated to a static control point – data sink in the network, using node to node - multi-hop data propagation. However, sensor devices consume significant amounts of energy in addition to increased implementation complexity, since a routing protocol is executed. Also, a point of failure emerges in the area near the control center where nodes relay the data from nodes that are farther away. Recently, a new approach has been developed that shifts the burden from the sensor nodes to the sink. The main idea is that the sink has significant and easily replenishable energy reserves and can move inside the area the sensor network is deployed, in order to acquire the data collected by the sensor nodes at very low energy cost. However, the need to visit all the regions of the network may result in large delivery delays.
In this work we have developed protocols that control the movement of the sink in wireless sensor networks with non-uniform deployment of the sensor nodes, in order to succeed an efficient (with respect to both energy and latency) data collection. More specifically, a graph formation phase is executed by the sink during the initialization: the network area is partitioned in equal square regions, where the sink, pauses for a certain amount of time, during the network traversal, in order to collect data.
We propose two network traversal methods, a deterministic and a random one. When the sink moves in a random manner, the selection of the next area to visit is done in a biased random manner depending on the frequency of visits of its neighbor areas. Thus, less frequently visited areas are favored. Moreover, our method locally determines the stop time needed to serve each region with respect to some global network resources, such as the initial energy reserves of the nodes and the density of the region, stopping for a greater time interval at regions with higher density, and hence more traffic load. In this way, we achieve accelerated coverage of the network as well as fairness in the service time of each region.Besides randomized mobility, we also propose an optimized deterministic trajectory without visit overlaps, including direct (one-hop) sensor-to-sink data transmissions only.
We evaluate our methods via simulation, in diverse network settings and comparatively to related state of the art solutions. Our findings demonstrate significant latency and energy consumption improvements, compared to previous research.
Abstract: Wireless sensor networks are a recently introduced category of ad hoc computer networks, which are comprised by nodes of small size and limited computing and energy resources. Such nodes are able of measuring physical properties such as temperature, humidity, etc., wireless communication between each other and in some cases interaction with their surrounding environments (through the use of electromechanical parts).
As these networks have begun to be widely available (in terms of cost and commercial hardware availability), their field of application and philosophy of use is constantly evolving. We have numerous examples of their applications, ranging from monitoring the biodiversity of a specific outdoor area to structural health monitoring of bridges, and also networks ranging from few tens of nodes to even thousands of nodes.
In this PhD thesis we investigated the following basic research lines related to wireless sensor networks:
a) their simulation,
b) the development of data propagation protocols suited to such networks and their evaluation through simulation,
c) the modelling of ``hostile'' circumstances (obstacles) during their operation and evaluation of their impact through simulation,
d) the development of a sensor network management application.
Regarding simulation, we initially placed an emphasis to issues such as the effective simulation of networks of several thousands of nodes, and in that respect we developed a network simulator (simDust), which is extendable through the addition of new data propagation protocols and visualization capabilities. This simulator was used to evaluate the performance of a number of characteristic data propagation protocols for wireless sensor networks. Furthermore, we developed a new protocol (VRTP) and evaluated its performance against other similar protocols. Our studies show that the new protocol, that uses dynamic changes of the transmission range of the network nodes, performs better in certain cases than other related protocols, especially in networks containing obstacles and in the case of non-homogeneous placement of nodes.
Moreover, we emphasized on the addition of ``realistic'' conditions to the simulation of such protocols, that have an adversarial effect on their operation. Our goal was to introduce a model for obstacles that adds little computational overhead to a simulator, and also study the effect of the inclusion of such a model on data propagation protocols that use geographic information (absolute or relative). Such protocols are relatively sensitive to dynamic topology changes and network conditions. Through our experiments, we show that the inclusion of obstacles during simulation can have a significant effect on these protocols.
Finally, regarding applications, we initially proposed an architecture (WebDust/ShareSense), for the management of such networks, that would provide basic capabilities of managing such networks and developing applications above it. Features that set it apart are the capability of managing multiple heterogeneous sensor networks, openess, the use of a peer-to-peer architecture for the interconnection of multiple sensor network. A large part of the proposed architecture was implemented, while the overall architecture was extended to also include additional visualization capabilities.
Abstract: Wireless sensor networks are comprised of a vast number of devices, situated in an area of interest that self organize in a structureless network, in order to monitor/record/measure an environmental variable or phenomenon and subsequently to disseminate the data to the control center.
Here we present research focused on the development, simulation and evaluation of energy efficient algorithms, our basic goal is to minimize the energy consumption. Despite technology advances, the problem of energy use optimization remains valid since current and emerging hardware solutions fail to solve it.
We aim to reduce communication cost, by introducing novel techniques that facilitate the development of new algorithms. We investigated techniques of distributed adaptation of the operations of a protocol by using information available locally on every node, thus through local choices we improve overall performance. We propose techniques for collecting and exploiting limited local knowledge of the network conditions. In an energy efficient manner, we collect additional information which is used to achieve improvements such as forming energy efficient, low latency and fault tolerant paths to route data. We investigate techniques for managing mobility in networks where movement is a characteristic of the control center as well as the sensors. We examine methods for traversing and covering the network field based on probabilistic movement that uses local criteria to favor certain areas.
The algorithms we develop based on these techniques operate a) at low level managing devices, b) on the routing layer and c) network wide, achieving macroscopic behavior through local interactions. The algorithms are applied in network cases that differ in density, node distribution, available energy and also in fundamentally different models, such as under faults, with incremental node deployment and mobile nodes. In all these settings our techniques achieve significant gains, thus distinguishing their value as tools of algorithmic design.
Abstract: Wireless sensor networks are comprised of a vast number of ultra-small fully autonomous computing, communication and sensing devices, with very restricted energy and computing capabilities, which co-operate to accomplish a large sensing task. Such networks can be very useful in practice in applications that require fine-grain monitoring of physical environment subjected to critical conditions (such as inaccessible terrains or disaster places). Very large numbers of sensor devices can be deployed in areas of interest and use self-organization and collaborative methods to form deeply networked environments. Features including the huge number of sensor devices involved, the severe power, computational and memory limitations, their dense deployment and frequent failures, pose new design and implementation aspects. The efficient and robust realization of such large, highly-dynamic, complex, non-conventional environments is a challenging algorithmic and technological task. In this work we consider certain important aspects of the design, deployment and operation of distributed algorithms for data propagation in wireless sensor networks and discuss some characteristic protocols, along with an evaluation of their performance.
Abstract: We propose a new data dissemination protocol for wireless sensor networks, that basically pulls some additional knowledge about the network in order to subsequently improve data forwarding towards the sink. This extra information is still local, limited and obtained in a distributed manner. This extra knowledge is acquired by only a small fraction of sensors thus the extra energy cost only marginally affects the overall protocol efficiency. The new protocol has low latency and manages to propagate data successfully even in the case of low densities. Furthermore, we study in detail the effect of failures and show that our protocol is very robust. In particular, we implement and evaluate the protocol using large scale simulation, showing that it significantly outperforms well known relevant solutions in the state of the art.
Abstract: Smart Dust is a set of a vast number of ultra-small fully autonomous computing and communication devices, with very restricted energy and computing capabilities, that co-operate to quickly and efficiently accomplish a large sensing task. Smart Dust can be very useful in practice, i.e., in the local detection of a remote crucial event and the propagation of data reporting its realization. In this work we make an effort towards the research on smart dust from an algorithmic point of view. We first provide a simple but realistic model for smart dust and present an interesting problem, which is how to propagate efficiently information on an event detected locally. Then we present various smart dust protocols for local detection and propagation that are simple enough to be implemented on real smart dust systems, and perform, under some simplifying assumptions, a rigorous average case analysis of their efficiency and energy consumption (and their interplay). This analysis leads to concrete results showing that our protocols are very efficient and robust. We also validate the analytical results by extensive experiments.
Abstract: Data collection is usually performed in wireless sensor networks by the sensors
relaying data towards a static control center (sink). Motivated by important
applications (mostly related to ambient intelligence and remote monitoring)
and as a first step towards introducing mobility, we propose the basic
idea of having a sink moving in the network area and collecting
data from sensors. We propose four characteristic mobility patterns
for the sink along with different data collection strategies. Through a
detailed simulation study, we evaluate several important performance properties of
each approach. Our findings demonstrate that by taking advantage
of the sink's mobility and shifting work from sensors to the powerful sink,
we can significantly reduce the energy spent in relaying traffic and thus greatly
extend the lifetime of the network.
Abstract: Through recent technology advances in the eld of wireless energy transmission, Wireless Rechargeable Sensor Networks
(WRSN) have emerged. In this new paradigm for
WSNs a mobile entity called Mobile Charger (MC) traverses
the network and replenishes the dissipated energy of sensors.
In this work we rst provide a formal de nition of the charging
dispatch decision problem and prove its computational
hardness. We then investigate how to optimize the tradeo
s of several critical aspects of the charging process such
as a) the trajectory of the charger, b) the di erent charging
policies and c) the impact of the ratio of the energy
the MC may deliver to the sensors over the total available
energy in the network. In the light of these optimizations,
we then study the impact of the charging process to the
network lifetime for three characteristic underlying routing
protocols; a greedy protocol, a clustering protocol and an
energy balancing protocol. Finally, we propose a Mobile
Charging Protocol that locally adapts the circular trajectory
of the MC to the energy dissipation rate of each sub-region
of the network. We compare this protocol against several
MC trajectories for all three routing families by a detailed
experimental evaluation. The derived ndings demonstrate
signi cant performance gains, both with respect to the no
charger case as well as the di erent charging alternatives; in
particular, the performance improvements include the network
lifetime, as well as connectivity, coverage and energy
balance properties.
Abstract: We call radiation at a point of a wireless network the total amount of electromagnetic quantity (energy or power density) the point is exposed to. The impact of radiation can be high and we believe it is worth studying and control; towards radiation aware wireless networking we take (for the first time in the study of this aspect) a distributed computing, algorithmic approach. We exemplify this line of research by focusing on sensor networks, studying the minimum radiation path problem of finding the lowest radiation trajectory of a person moving from a source to a destination point in the network region. For this problem, we sketch the main ideas behind a linear program that can provide a tight approximation of the optimal solution, and then we discuss three heuristics that can lead to low radiation paths. We also plan to investigate the impact of diverse node mobility to the heuristics' performance.
Abstract: We study the important problem of tracking moving
targets in wireless sensor networks. We try to overcome the
limitations of standard state of the art tracking methods based on
continuous location tracking, i.e. the high energy dissipation and
communication overhead imposed by the active participation of
sensors in the tracking process and the low scalability, especially
in sparse networks. Instead, our approach uses sensors in a
passive way: they only record and judiciously spread information
about observed target presence in their vicinity; this information
is then used by the (powerful) tracking agent to locate the target
by just following the traces left at sensors. Our protocol is greedy,
local, distributed, energy efficient and very successful, in the
sense that (as shown by extensive simulations) the tracking agent
manages to quickly locate and follow the target; also, we achieve
good trade-offs between the energy dissipation and latency.
Abstract: We investigate the problem of ecient wireless energy recharging in Wireless Rechargeable Sensor Networks (WRSNs). In
such networks special mobile entities (called the Mobile Chargers) traverse the network and wirelessly replenish the energy
of sensor nodes. In contrast to most current approaches, we envision methods that are distributed and use limited network
information. We propose four new protocols for ecient recharging, addressing key issues which we identify, most notably (i)
what are good coordination procedures for the Mobile Chargers and (ii) what are good trajectories for the Mobile Chargers.
Two of our protocols (
DC,DCLK
) perform distributed, limited network knowledge coordination and charging, while two others
(
CC,CCGK
) perform centralized, global network knowledge coordination and charging. As detailed simulations demonstrate,
one of our distributed protocols outperforms a known state of the art method, while its performance gets quite close to the
performance of the powerful centralized global knowledge method.
Abstract: As the Internet of Things (IOT) arises, the use of
low-end devices on a daily basis increases. The wireless nature
of communication that these devices provide raises security and
privacy issues. For protecting a user’s privacy, cryptography
offers the tool of zero knowledge proofs (ZKP). In this
paper, we study well-established ZKP protocols based on the
discrete logarithm problem and we adapt them to the Elliptic
Curve Cryptography (ECC) setting, which consists an ideal
candidate for embedded implementations. Then, we implement
the proposed protocols on Wiselib, a generic and open source
algorithmic library. For the first time, we present a thorough
evaluation of the protocols on two popular hardware platforms
equipped with low end microcontrollers (Jennic JN5139, TI
MSP430) and 802.15.4 RF transceivers, in terms of code size,
execution time, message size and energy requirements. This
work’s results can be used from developers who wish to achieve
certain levels of privacy in their applications.
Abstract: Few IoT systems monitoring energy consumption in buildings have focused on the educational community. IoT in the educational domain can jump-start a process of sustainability awareness and behavioral change towards energy savings, as well as provide tangible financial savings. We present a real-world multi-site IoT deployment, comprising 19 school buildings, aiming at enabling IoT-based energy awareness and sustainability lectures, promoting energy-saving behaviors supported by IoT data. We discuss scenarios where IoT-enabled applications are integrated into school life, providing an engaging and hands-on approach, based on real data, generating value in terms of educational and energy savings outcomes. We also present a set of first results, based on the analysis of school-building data, which highlight potential ways to identify irregularities and inefficiencies.
Abstract: In this work we study the problem of scheduling tasks with dependencies in multiprocessor architectures where processors have different speeds.
We present the preemptive algorithm "Save-Energy" that given a schedule of tasks it post processes it to improve the energy efficiency without any deterioration of the makespan. In terms of time efficiency, we show that preemptive scheduling in an asymmetric system can achieve the same or better optimal makespan than in a symmetric system. Motivited by real multiprocessor systems, we investigate architectures that exhibit limited asymmetry: there are two essentially different speeds. Interestingly, this special case has not been studied in the field of parallel computing and scheduling theory; only the general case was studied where processors have K essentially different speeds. We present the non-preemptive algorithm "Remnants'' that achieves almost optimal makespan. We provide a refined analysis of a recent scheduling method. Based on this analysis, we specialize the scheduling policy and provide an algorithm of (3 + o(1)) expected approximation factor. Note that this improves the previous best factor (6 for two speeds). We believe that our work will convince researchers to revisit this well studied scheduling problem for these simple, yet realistic, asymmetric multiprocessor architectures.
Abstract: We study the problem of energy-balanced data propagation
in wireless sensor networks. The energy balance property
guarantees that the average per sensor energy dissipation
is the same for all sensors in the network, during
the entire execution of the data propagation protocol. This
property is important since it prolongs the network˘s lifetime
by avoiding early energy depletion of sensors.
We propose a new algorithm that in each step decides
whether to propagate data one-hop towards the final destination
(the sink), or to send data directly to the sink. This
randomized choice balances the (cheap) one-hop transimssions
with the direct transimissions to the sink, which are
more expensive but “bypass” the sensors lying close to the
sink. Note that, in most protocols, these close to the sink
sensors tend to be overused and die out early.
By a detailed analysis we precisely estimate the probabilities
for each propagation choice in order to guarantee
energy balance. The needed estimation can easily be performed
by current sensors using simple to obtain information.
Under some assumptions, we also derive a closed form
for these probabilities.
The fact (shown by our analysis) that direct (expensive)
transmissions to the sink are needed only rarely, shows that
our protocol, besides energy-balanced, is also energy efficient.
Abstract: We study the problem of energy-balanced data propagation in wireless sensor networks. The energy balance property guarantees that the average per sensor energy dissipation is the same for all sensors in the network, during the entire execution of the data propagation protocol. This property is important since it prolongs the network˘:s lifetime by avoiding early energy depletion of sensors.
We propose a new algorithm that in each step decides whether to propagate data one-hop towards the final destination (the sink), or to send data directly to the sink. This randomized choice balances the (cheap) one-hop transimssions with the direct transimissions to the sink, which are more expensive but “bypass” the sensors lying close to the sink. Note that, in most protocols, these close to the sink sensors tend to be overused and die out early.
By a detailed analysis we precisely estimate the probabilities for each propagation choice in order to guarantee energy balance. The needed estimation can easily be performed by current sensors using simple to obtain information. Under some assumptions, we also derive a closed form for these probabilities.
The fact (shown by our analysis) that direct (expensive) transmissions to the sink are needed only rarely, shows that our protocol, besides energy-balanced, is also energy efficient.
Abstract: The energy balance property (i.e., all nodes having the same energy throughout the network evolution) contributes significantly (along with energy efficiency) to the maximization of the network lifespan and network connectivity. The problem of achieving energy balanced propagation is well studied in static networks, as it has attracted a lot of research attention.
Recent technological advances have enabled sensor devices to be attached to mobile entities of our every day life (e.g. smart-phones, cars, PDAs etc), thus introducing the formation of highly mobile sensor networks.
Inspired by the aforementioned applications, this work is (to the best of our knowledge) the first studying the energy balance property in wireless networks where the nodes are highly and dynamically mobile. In particular, in this paper we propose a new diverse mobility model which is easily parameterized and we also present a new protocol which tries to adaptively exploit the inherent node mobility in order to achieve energy balance in the network in an efficient way.
Abstract: Wireless Sensor Networks are comprised of a vast number of ultra-small, autonomous computing and communication devices, with restricted energy, that co-operate to accomplish a large sensing task. In this work: a) We propose extended versions of two data propagation protocols for such networks: the Sleep-Awake Probabilistic Forwarding Protocol (SW-PFR) and the Hierarchical Threshold sensitive Energy Efficient Network protocol (H-TEEN). These non-trivial extensions improve the performance of the original protocols, by introducing sleep-awake periods in the PFR protocol to save energy, and introducing a hierarchy of clustering in the TEEN protocol to better cope with large networks, b) We implemented the two protocols and performed an extensive simulation comparison of various important measures of their performance with a focus on energy consumption, c) We investigate in detail the relative advantages and disadvantages of each protocol, d) We discuss a possible hybrid combination of the two protocols towards optimizing certain goals.
Abstract: In this work we study energy efficient routing strategies
for wireless ad-hoc networks. In this kind of networks,
energy is a scarce resource and its conservation
and efficient use is a major issue. Our strategy follows
the multi-cost routing approach, according to which a
cost vector of various parameters is assigned to each
link. The parameters of interest are the number of hops
on a path, and the residual energy and the transmission
power of the nodes on the path. These parameters
are combined in various optimization functions,
corresponding to different routing algorithms, for selecting
the optimal path. We evaluate the routing algorithms
proposed in a number of scenarios, with respect
to energy consumption, throughput and other performance
parameters of interest. From the experiments
conducted we conclude that routing algorithms that take
into account energy related parameters, increase the
lifetime of the network, while achieving better performance
than other approaches, such as minimum hop
routing.
Abstract: In this work, we propose an energy-efficient multicasting algorithm
for wireless networks for the case where the transmission
powers of the nodes are fixed. Our algorithm is
based on the multicost approach and selects an optimal
energy-efficient set of nodes for multicasting, taking into account:
i) the node residual energies, ii) the transmission
powers used by the nodes, and iii) the set of nodes covered.
Our algorithm is optimal, in the sense that it can
optimize any desired function of the total power consumed
by the multicasting task and the minimum of the current
residual energies of the nodes, provided that the optimization
function is monotonic in each of these parameters. Our
optimal algorithm has non-polynomial complexity, thus, we
propose a relaxation producing a near-optimal solution in
polynomial time. The performance results obtained show
that the proposed algorithms outperform established solutions
for energy-aware multicasting, with respect to both
energy consumption and network lifetime. Moreover, it is
shown that the near-optimal multicost algorithm obtains
most of the performance benefits of the optimal multicost
algorithm at a smaller computational overhead.
Abstract: A crucial issue in wireless networks is to support efficiently communication patterns that are typical in traditional (wired) networks. These include broadcasting, multicasting, and gossiping (all-to-all communication). In this work we study such problems in static ad hoc networks. Since, in ad hoc networks, energy is a scarce resource, the important engineering question to be solved is to guarantee a desired communication pattern minimizing the total energy consumption. Motivated by this question, we study a series of wireless network design problems and present new approximation algorithms and inapproximability results.
Abstract: Raising awareness among young people, and especially students, on the relevance of behavior change for achieving energy savings is increasingly being considered as a key enabler towards long-term and cost-effective energy efficiency policies. However, the way to successfully apply educational interventions focused on such targets inside schools is still an open question. In this paper, we present our approach for enabling IoT-based energy savings and sustainability awareness lectures and promoting data-driven energy-saving behaviors focused on a high school audience. We present our experiences toward the successful application of sets of educational tools and software over a real-world Internet of Things (IoT) deployment. We discuss the use of gamification and competition as a very effective end-user engagement mechanism for school audiences. We also present the design of an IoT-based hands-on lab activity, integrated within a high school computer science curriculum utilizing IoT devices and data produced inside the school building, along with the Node-RED platform. We describe the tools used, the organization of the educational activities and related goals. We report on the experience carried out in both directions in a high school in Italy and conclude by discussing the results in terms of achieved energy savings within an observation period.
Abstract: Several networking technologies targeting the IoT application space currently compete within the smart city domain, both in outdoor and indoor deployments. However, up till now, there is no clear winner, and results from real-world deployments have only recently started to surface. In this paper, we present a comparative study of 2 popular IoT networking technologies, LoRa and IEEE 802.15.4, within the context of a research-oriented IoT deployment inside school buildings in Europe, targeting energy efficiency in education. We evaluate the actual performance of these two technologies in real-world settings, presenting a comparative study on the effect of parameters like the built environment, network quality, or data rate. Our results indicate that both technologies have their advantages, and while in certain cases both are perfectly adequate, in our use case LoRa exhibits a more robust behavior. Moreover, LoRa˘s characteristics make it a very good choice for indoor IoT deployments such as in educational buildings, and especially in cases where there are low bandwidth requirements.
Abstract: Energy is a scarce resource in ad hoc wireless networks and it
is of paramount importance to use it e±ciently when establishing com-
munication patterns. In this work we study algorithms for computing
energy-e±cient multicast trees in ad hoc wireless networks. Such algo-
rithms either start with an empty solution which is gradually augmented
to a multicast tree (augmentation algorithms) or take as input an initial
multicast tree and `walk' on di®erent multicast trees for a Żnite number
of steps until some acceptable decrease in energy consumption is achieved
(local search algorithms).
We mainly focus on augmentation algorithms and in particular we have
implemented a long list of existing such algorithms in the literature and
new ones. We experimentally compare all these algorithms on random
geometric instances of the problem and obtain results in terms of the
energy e±ciency of the solutions obtained. Additional results concerning
the running time of our implementations are also presented. We also ex-
plore how much the solutions obtained by augmentation algorithms can
be improved by local search algorithms. Our results show that one of our
new algorithms and its variations achieve the most energy-e±cient solu-
tions while being very fast. Our investigations shed some light to those
properties of geometric instances of the problem which make augmenta-
tion algorithms perform well.
Abstract: We present key aspects (hardware, software, topology, networking) of SenseWall, an experimental sensor network test-bed we have created for the implementation and engineering of distributed sensor network algorithms. We then describe how SenseWall has been in particular used to implement two recent state of the art algorithms for energy balanced sensor data propagation. We elaborate on the issues and challenges created by the restrictions and particularities of the experimental test-bed and how we dealt with them. We also carry out a detailed performance evaluation comparing the energy balance protocols to two baseline protocols that include only either single hop or direct data transmissions.
Abstract: We investigate the impact of multiple, mobile sinks on
efficient data collection in wireless sensor networks. To
improve performance, our protocol design focuses on minimizing
overlaps of sink trajectories and balancing the service load
among the sinks. To cope with high network dynamics, placement
irregularities and limited network knowledge we propose three different
protocols: a) a centralized one, that explicitly equalizes spatial coverage;
this protocol assumes strong modeling assumptions, and also serves as a kind
of performance lower bound in uniform networks of low dynamics b)
a distributed protocol based on mutual avoidance of sinks c) a clustering
protocol that distributively groups service areas towards balancing the load per sink.
Our simulation findings demonstrate significant gains in latency, while keeping the success
rate and the energy dissipation at very satisfactory levels even under
high network dynamics and deployment heterogeneity.
Abstract: We study the problem of fast and energy-efficient
data collection of sensory data using a mobile sink, in wireless sensor networks in which both the sensors and the sink move. Motivated by relevant applications, we focus on dynamic sensory
mobility and heterogeneous sensor placement. Our approach basically suggests to exploit the sensor motion to adaptively propagate information based on local conditions (such as high placement concentrations), so that the sink gradually ”learns”
the network and accordingly optimizes its motion. Compared to relevant solutions in the state of the art (such as the blind random walk, biased walks, and even optimized deterministic sink mobility), our method significantly reduces latency (the improvement ranges from 40% for uniform placements, to 800% for heterogeneous ones), while also improving the success rate and keeping the energy dissipation at very satisfactory levels.
Abstract: We propose a new data dissemination protocol for wireless sensor networks, that basically pulls some additional knowledge about the network in order to subsequently improve data forwarding towards the sink. This extra information is still local, limited and obtained in a distributed manner. This extra knowledge is acquired by only a small fraction of sensors thus the extra energy cost only marginally affects the overall protocol efficiency. The new protocol has low latency and manages to propagate data successfully even in the case of low densities. Furthermore, we study in detail the effect of failures and show that our protocol is very robust. In particular, we implement and evaluate the protocol using large scale simulation, showing that it significantly outperforms well known relevant solutions in the state of the art.
Abstract: Green Awareness in Action (GAIA) is introducing game challenges to the school community, where real-world sensor data produced inside school buildings are used,
aiming to increase awareness and reduce energy consumption. An initial small-scale in-school evaluation trial of the games˘ deployment is reported here.
Abstract: Educational buildings constitute 17% of the non-residential building stock in the EU [1], while recent work shows that a focus on energy use in schools can potentially yield an array of rewards, in concert with educational excellence and a healthy learning environment [2].
Having these in mind, GAIA1, a Horizon2020 EC-funded project, is developing an IoT platform
that combines sensing, web-based and gamification elements, in order to address the
educational community. Its primary aim is to increase awareness about energy consumption
and sustainability, based on real sensor data produced by the school buildings where students and teachers live and work, while also lead towards behavior change in terms of energy efficiency.
Abstract: The Internet of Things is shaping up to be the ideal vehicle for introducing pervasive computing in our everyday lives, especially in the form of smart home and building management systems. However, although such technologies are gradually becoming more mainstream, there is still a lot of ground to be covered with respect to public buildings and specifically ones in the educational sector. We discuss here \Green Mindset", an action focusing on energy efficiency and
sustainability in Greek public schools. A large-scale sensor infrastructure has been deployed to 12 public school buildings across diverse settings. We report on the overall design and implementation of the system, as well as on some first results coming from the data produced. Our system provides a flexible and efficient basis for realizing a unified approach to monitoring energy consumption and environmental parameters,
that can be used both for building administration
and educational purposes.
Abstract: In this work we study the implementation of multicost rout-
ing in a distributed way in wireless mobile ad hoc networks.
In contrast to traditional single-cost routing, where each
path is characterized by a scalar, in multicost routing a
vector of cost parameters is assigned to each network link,
from which the cost vectors of candidate paths are calcu-
lated. These parameters are combined in various optimiza-
tion functions, corresponding to different routing algorithms,
for selecting the optimal path. Up until now the performance
of multicost and multi-constrained routing in wireless ad hoc
networks has been evaluated either at a theoretical level or
by assuming that nodes are static and have full knowledge
of the network topology and nodes� state. In the present
paper we assess the performance of multicost routing based
on energy-related parameters in mobile ad hoc networks by
embedding its logic in the Dynamic Source Routing (DSR)
algorithm, which is a well-known fully distributed routing
algorithm. We use simulations to compare the performance
of the multicost-DSR algorithm to that of the original DSR
algorithm and examine their behavior under various node
mobility scenarios. The results confirm that the multicost-
DSR algorithm improves the performance of the network in
comparison to the original DSR algorithm in terms of energy efficiency. The multicost-DSR algorithm enhances the
performance of the network not only by reducing energy
consumption overall in the network, but also by spreading
energy consumption more uniformly across the network, pro
longing the network lifetime and reducing the packet drop
probability. Furthermore the delay suffered by the packets
reaching their destination for the case of the multicost-DSR
algorithm is shown to be lower than in the case of the orig
inal DSR algorithm.
Abstract: In this work we study the combination of multicost
routing and adjustable transmission power in wireless
ad hoc networks, so as to obtain dynamic energy- and
interference-efficient routes to optimize network performance.
In multi-cost routing, a vector of cost parameters is
assigned to each network link, from which the cost vectors
of candidate paths are calculated. Only at the end these
parameters are combined in various optimization functions,
corresponding to different routing algorithms, for selecting
the optimal path. The multi-cost routing problem is a
generalization of the multi-constrained problem, where no
constraints exist, and is also significantly more powerful
than single-cost routing. Since energy is an important
limitation of wireless communications, the cost parameters
considered are the number of hops, the interference caused,
the residual energy and the transmission power of the
nodes on the path; other parameters could also be included,
as desired. We assume that nodes can use power control to
adjust their transmission power to the desired level. The
experiments conducted show that the combination of multicost
routing and adjustable transmission power can lead to
reduced interference and energy consumption, improving
network performance and lifetime.
Abstract: Recent rapid developments in micro-electro-mechanical systems
(MEMS), wireless communications and digital electronics have already
led to the development of tiny, low-power, low-cost sensor devices.
Such devices integrate sensing, limited data processing and restricted
communication capabilities.
Each sensor device individually might have small utility, however the
effective distributed co-ordination of large numbers of such devices can
lead to the efficient accomplishment of large sensing tasks. Large numbers
of sensors can be deployed in areas of interest (such as inaccessible
terrains or disaster places) and use self-organization and collaborative
methods to form an ad-hoc network.
We note however that the efficient and robust realization of such large,
highly-dynamic, complex, non-conventional networking environments is
a challenging technological and algorithmic task, because of the unique
characteristics and severe limitations of these devices.
This talk will present and discuss several important aspects of the
design, deployment and operation of sensor networks. In particular, we
provide a brief description of the technical specifications of state-of-theart
sensor, a discussion of possible models used to abstract such networks,
a discussion of some key algorithmic design techniques (like randomization,
adaptation and hybrid schemes), a presentation of representative
protocols for sensor networks, for important problems including data
propagation, collision avoidance and energy balance and an evaluation
of crucial performance properties (correctness, efficiency, fault-tolerance)
of these protocols, both with analytic and simulation means.
Abstract: In this paper we propose an energy-aware broadcast algorithm for wireless networks. Our algorithm is based on the multicost approach and selects the set of nodes that by transmitting implement broadcasting in an optimally energy-efficient way. The energy-related parameters taken into account are the node transmission power and the node residual energy. The algorithm{\^a}€™s complexity however is non-polynomial, and therefore, we propose a relaxation producing a near-optimal solution in polynomial time. We also consider a distributed information exchange scheme that can be coupled with the proposed algorithms and examine the overhead introduced by this integration. Using simulations we show that the proposed algorithms outperform other solutions in the literature in terms of energy efficiency. Moreover, it is shown that the near-optimal algorithm obtains most of the performance benefits of the optimal algorithm at a smaller computational overhead.
Abstract: We propose a class of novel energy-efficient multi-cost routing algorithms for wireless mesh networks, and evaluate their performance. In multi-cost routing, a vector of cost parameters is assigned to each network link, from which the cost vectors of candidate paths are calculated using appropriate operators. In the end these parameters are combined in various optimization functions, corresponding to different routing algorithms, for selecting the optimal path. We evaluate the performance of the proposed energy-aware multi-cost routing algorithms under two models. In the network evacuation model, the network starts with a number of packets that have to be transmitted and an amount of energy per node, and the objective is to serve the packets in the smallest number of steps, or serve as many packets as possible before the energy is depleted. In the dynamic one-to-one communication model, new data packets are generated continuously and nodes are capable of recharging their energy periodically, over an infinite time horizon, and we are interested in the maximum achievable steady-state throughput, the packet delay, and the energy consumption. Our results show that energy-aware multi-cost routing increases the lifetime of the network and achieves better overall network performance than other approaches.
Abstract: In this work we study the combination of
multicost routing and adjustable transmission power
in wireless ad-hoc networks, so as to obtain dynamic
energy and interference-efficient routes to optimize network performance. In multi-cost routing, a vector of
cost parameters is assigned to each network link, from
which the cost vectors of candidate paths are calcu-
lated. Only at the end are these parameters combined in
various optimization functions, corresponding to different routing algorithms, for selecting the optimal path.
The multi-cost routing problem is a generalization of
the multi-constrained problem, where no constraints exist, and is also significantly more powerful than single-
cost routing. Since energy is an important limitation of
wireless communications, the cost parameters consid
ered are the number of hops, the interference caused,
the residual energy and the transmission power of the
nodes on the path; other parameters could also be in
cluded, as desired.We assume that nodes can use power
control to adjust their transmission power to the desired
level. The experiments conducted show that the com
bination of multi-cost routing and adjustable transmis sion power can lead to reduced interference and energy
consumption, improving network performance and life-
time.
Abstract: In this work we study the dynamic one-to-one communica-
tion problem in energy- and capacity-constrained wireless ad-hoc net-
works. The performance of such networks is evaluated under random
traffic generation and continuous energy recharging at the nodes over an
infinite-time horizon.We are interested in the maximum throughput that
can be sustained by the network with the node queues being finite and in
the average packet delay for a given throughput. We propose a multicost
energy-aware routing algorithm and compare its performance to that of
minimum-hop routing. The results of our experiments show that gener-
ally the energy-aware algorithm achieves a higher maximum throughput
than the minimum-hop algorithm. More specifically, when the network
is mainly energy-constrained and for the 2-dimensional topology consid-
ered, the throughput of the proposed energy-aware routing algorithm is
found to be almost twice that of the minimum-hop algorithm.
Abstract: We present and discuss challenges and solutions posed by the design of an
adaptable network infrastructure of tiny artifacts. Such artifacts are characterized by
severe limitations in computational power, communications capacity and energy;
nevertheless they must realize a communication infrastructure able to deliver
services to the end-users in a very dynamic and challenging environment. Namely
we present one unifying scenario for the activities of the FRONTS project
(www.fronts.cti.gr). The aim of the unifying scenario is to show how the results
achieved in the project can be exploited to build such a communication
infrastructure.
Abstract: Geographic routing scales well in sensor networks, mainly
due to its stateless nature. Still, most of the algorithms are
concerned with finding some path, while the optimality of
the path is difficult to achieve. In this paper we are presenting
a novel geographic routing algorithm with obstacle
avoidance properties. It aims at finding the optimal path
from a source to a destination when some areas of the network
are unavailable for routing due to low local density or
obstacle presence. It locally and gradually with time (but,
as we show, quite fast) evaluates and updates the suitability
of the previously used paths and ignores non optimal paths
for further routing. By means of extensive simulations, we
are comparing its performance to existing state of the art
protocols, showing that it performs much better in terms of
path length thus minimizing latency, space, overall traffic
and energy consumption.
Abstract: Motivated by the problem of efficiently collecting data from
wireless sensor networks via a mobile sink, we present an accelerated
random walk on Random Geometric Graphs. Random
walks in wireless sensor networks can serve as fully local,
very simple strategies for sink motion that significantly
reduce energy dissipation but introduce higher latency in the
data collection process. While in most cases random walks
are studied on graphs like Gn,p and Grid, we define and experimentally
evaluate our newly proposed random walk on
the Random Geometric Graphs model, that more accurately
abstracts spatial proximity in a wireless sensor network. We
call this new random walk the \~{a}-stretched random walk, and
compare it to two known random walks; its basic idea is
to favour visiting distant neighbours of the current node
towards reducing node overlap. We also define a new performance
metric called Proximity Cover Time which, along
with other metrics such as visit overlap statistics and proximity
variation, we use to evaluate the performance properties
and features of the various walks.
Abstract: We investigate the problem of how to achieve energy balanced data propagation in distributed wireless sensor networks. The energy balance property guarantees that the average per sensor energy dissipation is the same for all sensors in the network, throughout the execution of the data propagation protocol. This property is crucial for prolonging the network lifetime, by avoiding early energy depletion of sensors.
We survey representative solutions from the state of the art. We first present a basic algorithm that in each step probabilistically decides whether to propagate data one-hop towards the final destination (the sink), or to send it directly to the sink. This randomized choice trades-off the (cheap, but slow) one-hop transmissions with the direct transmissions to the sink, which are more expensive but bypass the bottleneck region around the sink and propagate data fast. By a detailed analysis using properties of stochastic processes and recurrence relations we precisely estimate (even in closed form) the probability for each propagation option necessary for energy balance.
The fact (shown by our analysis) that direct (expensive) transmissions to the sink are needed only rarely, shows that our protocol, besides energy balanced, is also energy efficient. We then enhance this basic result by surveying some recent findings including a generalized algorithm and demonstrating the optimality of this two-way probabilistic data propagation, as well as providing formal proofs of the energy optimality of the energy balance property.
Abstract: One oft-cited strategy towards sustainability is improving energy efficiency inside public buildings. In this context, the educational buildings sector presents a very interesting and important case for the monitoring and management of buildings, since it addresses both energy and educational issues. In this work, we present and discuss the hardware IoT infrastructure substrate that provides real-time monitoring in multiple school buildings. We believe that such a system needs to follow an open design approach: rely on hardware-agnostic components that communicate over well-defined open interfaces. We present in detail the design of our hardware components, while also providing insights to the overall system design and a first set of results on their operation. The presented hardware components are utilized as the core hardware devices for GAIA, an EU research project aimed at the educational community. As our system has been deployed and tested in several public school buildings in Greece, we also report on its validation.
Abstract: In this paper we propose an energy-efficient broadcast algorithm for wireless networks for the case where the transmission powers of the nodes are fixed. Our algorithm is based on the multicost approach and selects an optimal energy-efficient set of nodes for broadcasting, taking into account: i) the node residual energies, ii) the transmission powers used by the nodes, and iii) the set of nodes that are covered by a specific schedule. Our algorithm is optimal, in the sense that it can optimize any desired function of the total power consumed by the broadcasting task and the minimum of the current residual energies of the nodes, provided that the optimization function is monotonic in each of these parameters. Our algorithm has non-polynomial complexity, thus, we propose a relaxation producing a near-optimal solution in polynomial time. Using simulations we show that the proposed algorithms outperform other established solutions for energy-aware broadcasting with respect to both energy consumption and network lifetime. Moreover, it is shown that the near-optimal multicost algorithm obtains most of the performance benefits of the optimal multicost algorithm at a smaller computational overhead.
Abstract: This paper studies the data gathering problem in wireless networks, where data generated at the nodes has to be collected at a single sink. We investigate the relationship between routing optimality and fair resource management. In particular, we prove that for energy balanced data propagation, Pareto optimal routing and flow maximization are equivalent, and also prove that flow maximization is equivalent to maximizing the network lifetime. We algebraically characterize the network structures in which energy balanced data flows are maximal. Moreover, we algebraically characterize communication links which are not used by an optimal flow. This leads to the characterization of minimal network structures supporting the maximal flows.
We note that energy balance, although implying global optimality, is a local property that can be computed efficiently and in a distributed manner. We suggest online distributed algorithms for energy balance in different optimal network structures and numerically show their stability in particular setting. We remark that although the results obtained in this paper have a direct consequence in energy saving for wireless networks they do not limit themselves to this type of networks neither to energy as a resource. As a matter of fact, the results are much more general and can be used for any type of network and different type of resources.
Abstract: This paper studies the data gathering problem in wireless networks, where data generated at the nodes has to be collected at a single sink. We investigate the relationship between routing optimality and fair resource management. In particular, we prove that for energy-balanced data propagation, Pareto optimal routing and flow maximization are equivalent, and also prove that flow maximization is equivalent to maximizing the network lifetime. We algebraically characterize the network structures in which energy-balanced data flows are maximal. Moreover, we algebraically characterize communication links which are not used by an optimal flow. This leads to the characterization of minimal network structures supporting the maximal flows.
We note that energy-balance, although implying global optimality, is a local property that can be computed efficiently and in a distributed manner. We suggest online distributed algorithms for energy-balance in different optimal network structures and numerically show their stability in particular setting. We remark that although the results obtained in this paper have a direct consequence in energy saving for wireless networks they do not limit themselves to this type of networks neither to energy as a resource. As a matter of fact, the results are much more general and can be used for any type of network and different types of resources.
Abstract: This Volume contains the 11 papers corresponding to poster and demo presentations
accepted to the 7th ACM/IEEE International Symposium on Modeling,
Analysis and Simulation ofWireless and Mobile Systems (MSWiM 04),
that is held October 4-6, 2004, in Venice, Italy.
MSWiM 2004 (http://www.cs.unibo.it/mswim2004/) is intended to provide
an international forum for original ideas, recent results and achievements on
issues and challenges related to mobile and wireless systems.
A Call for Posters was announced and widely disseminated, soliciting posters
that report on recent original results or on-going research in the area of wireless
and mobile networks. Prospective authors were encouraged to submit interesting
results on all aspects of modeling, analysis and simulation of mobile and
wireless networks and systems. The scope and topics of the Posters Session
were the same as those included in the MSWiM Call for Papers (see above).
Poster presentations were meant to provide authors with early feedback on
their research work and enable them to present their research and exchange
ideas during the Symposium.
All submissions to the call for posters as well as selected papers submitted
to MSWiM 04 were considered and reviewed. The review process resulted in
accepting the set of 11 papers included in this Volume. Accepted posters will
also be on display during the Symposium.
The set of papers in this Proceedings covers a wide range of important topics
in wireless and mobile computing, including channel allocation in wireless
networks, quality of service provisioning in IEEE 802.11 wireless LANs, IP
mobility support, energy conservation, routing in mobile adhoc networks, resource
sharing, wireless access to the WWW, sensor networks etc. The performance
evaluation techniques used include both analysis and simulation.
We hope that the poster papers included in this Volume will facilitate a fruitful
and lively discussion and exchange of interesting and creative ideas during
the Symposium.
We wish to thank the MSWiM Steering Committee Chair Azzedine Boukerche
and the Program Co-Chairs ofMSWiM 04 Carla-Fabiana Chiasserini and
Lorenzo Donatiello for their valuable help in the selection procedure. Also, the
MSWiM 04 Publicity Co-Chairs Luciano Bononi, Helen Karatza and Mirela
Sechi Moretti Annoni Notare for disseminating the Call for Posters.
We wish to warmly thank the Poster Proceedings Chair Ioannis Chatzigiannakis
for carefully doing an excellent job in preparing the Volume you now
hold in your hands.
Abstract: We propose, implement and evaluate new energy conservation schemes for efficient data propagation in wireless sensor networks. Our protocols are adaptive, i.e. locally monitor the network conditions and accordingly adjust towards optimal operation choices. This dynamic feature is particularly beneficial in heterogeneous settings and in cases of redeployment of sensor devices in the network area. We implement our protocols and evaluate their performance through a detailed simulation study using our extended version of ns-2. In particular we combine our schemes with known communication paradigms. The simulation findings demonstrate significant gains and good trade-offs in terms of delivery success, delay and energy dissipation.
Abstract: Recent rapid technological developments have led to the
development of tiny, low-power, low-cost sensors. Such devices
integrate sensing, limited data processing and communication
capabilities.The effective distributed collaboration
of large numbers of such devices can lead to the efficient
accomplishment of large sensing tasks.
This talk focuses on several aspects of energy efficiency.
Two protocols for data propagation are studied: the first
creates probabilistically optimized redundant data transmissions
to combine energy efficiency with fault tolerance,
while the second guarantees (in a probabilistic way) the
same per sensor energy dissipation, towards balancing the
energy load and prolong the lifetime of the network.
A third protocol (in fact a power saving scheme) is also
presented, that directly and adaptively affects power dissipation
at each sensor. This “lower level” scheme can be
combined with data propagation protocols to further improve
energy efficiency.
Abstract: Wireless sensor networks are composed of a vast number of ultra-small, fully autonomous computing, communication, and sensing devices, with very restricted energy and computing capabilities, that cooperate to accomplish a large sensing task. Such networks can be very useful in practice. The authors propose extended versions of two data propagation protocols: the Sleep-Awake Probabilistic Forwarding (SW-PFR) protocol and the Hierarchical Threshold-Sensitive Energy-Efficient Network (H-TEEN) protocol. These nontrivial extensions aim at improving the performance of the original protocols by introducing sleep-awake periods in the PFR case to save energy and introducing a hierarchy of clustering in the TEEN case to better cope with large network areas. The authors implemented the two protocols and performed an extensive comparison via simulation of various important measures of their performance with a focus on energy consumption. Data propagation under this approach exhibits high fault tolerance and increases network lifetime.
Abstract: Wireless sensor networks are composed of a vast number of ultra-small, fully autonomous computing, communication, and sensing devices, with very restricted energy and computing capabilities, that cooperate to accomplish a large sensing task. Such networks can be very useful in practice. The authors propose extended versions of two data propagation protocols: the Sleep-Awake Probabilistic Forwarding (SW-PFR) protocol and the Hierarchical Threshold-Sensitive Energy-Efficient Network (H-TEEN) protocol. These nontrivial extensions aim at improving the performance of the original protocols by introducing sleep-awake periods in the PFR case to save energy and introducing a hierarchy of clustering in the TEEN case to better cope with large network areas. The authors implemented the two protocols and performed an extensive comparison via simulation of various important measures of their performance with a focus on energy consumption. Data propagation under this approach exhibits high fault tolerance and increases network lifetime.
Abstract: Wireless sensor and actor networks are comprised of a large number of small, fully autonomous computing, communication, sensing and actuation devices, with very restricted energy and computing capabilities. Such devices co-operate to accomplish a large sensing and acting task. Sensors gather information for an event in the physical world and notify the actors that perform appropriate actions by making a decision on receipt of the sensed information. Such networks can be very useful in practice i.e.~in the local detection of remote crucial events and the propagation of relevant data to decision
centers that perform appropriate actions upon the environment, thus realizing sensing and acting from a distance.
In this work we present a communication protocol that enables scalable, energy efficient and fault tolerant coordination while allowing to prioritize sensing tasks in situated wireless sensor and actor networks. The sensors react locally on environment and context changes and interact with each other in order to adjust the performance of the network in terms of energy, latency and success rate on a per-task basis. To deal with the increased complexity of such large-scale systems, our protocol pulls some additional knowledge about the network in order to subsequently improve data forwarding towards the actors.
We implement and evaluate the protocol using large scale simulation, showing its suitability in networks where sensor to actor and actor to actor coordination are important for accomplishing tasks of different priorities.
Abstract: In this work we focus on the energy efficiency challenge in wireless sensor networks, from both an on-line perspective (related to routing), as well as a network design perspective (related to tracking). We investigate a few representative, important aspects of energy efficiency: a) the robust and fast data propagation b) the problem of balancing the energy
dissipation among all sensors in the network and c) the problem of efficiently tracking moving
entities in sensor networks. Our work here is a methodological survey of selected results that
have alre dy appeared in the related literature.
In particular, we investigate important issues of energy optimization, like minimizing the total
energy dissipation, minimizing the number of transmissions as well as balancing the energy
load to prolong the system˘s lifetime. We review characteristic protocols and techniques in the recent literature, including probabilistic forwarding and local optimization methods. We study the problem of localizing and tracking multiple moving targets from a network design perspective i.e. towards estimating the least possible number of sensors, their positions and operation characteristics needed to efficiently perform the tracking task. To avoid an expensive massive deployment, we try to take advantage of possible coverage overlaps over space and time, by introducing a novel combinatorial model that captures such overlaps. Under this model, we abstract the tracking network design problem by a covering combinatorial problem and then design and analyze an efficient approximate method for sensor placement
and operation.
Abstract: In this work we present three new distributed, probabilistic data propagation protocols for Wireless Sensor Networks which aim at maximizing the network's operational life and improve its performance. The keystone of these protocols' design is fairness which declares that fair portions of network's work load should be assigned to each node, depending on their role in the system. All the three protocols, EFPFR, MPFR and TWIST, emerged from the study of the rigorously analyzed protocol PFR. Its design elements were identified and improvements were suggested and incorporated into the introduced protocols. The experiments conducted show that our proposals manage to improve PFR's performance in terms of success rate, total amount of energy saved, number of alive sensors and standard deviation of the energy left. Indicatively we note that while PFR's success rate is 69.5%, TWIST is achieving 97.5% and its standard deviation of energy is almost half of that of PFR.
Abstract: The sensor devices are battery powered thus energy is the most precious resource of a wireless sensor
network since periodically replacing the battery of the nodes in large scale deployments is infeasible. The
collected data is disseminated to a static control point { data sink in the network, using node to node
{ multi-hop data propagation, [4, 6]. However, sensor devices consume signi cant amounts of energy in
addition to increased implementation complexity since a routing protocol is executed. Also, a point of
failure emerges in the area near the control center where nodes relay the data from nodes that are farther
away
Abstract: Data propagation in wireless sensor
networks is usually performed as a multihop process.
Thus,
To deliver a single
message, the resources of many sensor nodes are used and
a lot of energy is spent.
Recently, a novel approach is catching momentum because of important applications;
that of having a mobile sink move inside the network area and collect
the data with low energy cost.
Here we extend this line of research by proposing and evaluating three new protocols.
Our protocols are novel in
a) investigating the impact of having {many} mobile sinks
b) in weak models with restricted mobility, proposing and evaluating
a mix of static and mobile sinks and c) proposing a distributed
protocol that tends to {equally spread the sinks} in the network to
further improve performance.
Our protocols are simple, based on randomization and assume locally
obtainable information. We perform an extensive evaluation via simulation; our
findings demonstrate that our solutions scale very well with respect to the number of sinks
and significantly reduce energy consumption and delivery delay.
Abstract: Raising awareness among young people and changing their behavior and habits concerning energy usage and the environment is key to achieving a sustainable planet. The goal to address the global climate problem requires informing the population on their roles in mitigation actions and adaptation of sustainable behaviors. Addressing climate change and achieve ambitious energy and climate targets requires a change in citizen behavior and consumption practices. IoT sensing and related scenario and practices, which address school children via discovery, gamification, and educational activities, are examined in this paper. Use of seawater sensors in STEM education, that has not previously been addressed, is included in these educational scenaria.
Abstract: In this work we study the problem of scheduling tasks with dependencies in multiprocessor architectures where processors have different speeds. We examine the energy-efficiency and time efficiency of scheduling in an asymmetric system.
Abstract: In this Phd thesis,, we try to use formal logic and threshold phenomena that asymptotically emerge with certainty in order to build new trust models and to evaluate the existing one. The departure point of our work is that dynamic, global computing systems are not amenable to a static viewpoint of the trust concept, no matter how this concept is formalized. We believe that trust should be a statistical, asymptotic concept to be studied in the limit as the system's components grow according to some growth rate. Thus, our main goal is to define trust as an emerging system property that ``appears'' or "disappears" when a set of properties hold, asymptotically with probability$ 0$ or $1$ correspondingly . Here we try to combine first and second order logic in order to analyze the trust measures of specific network models. Moreover we can use formal logic in order to determine whether generic reliability trust models provide a method for deriving trust between peers/entities as the network's components grow. Our approach can be used in a wide range of applications, such as monitoring the behavior of peers, providing a measure of trust between them, assessing the level of reliability of peers in a network. Wireless sensor networks are comprised of a vast number of ultra-small autonomous computing, communication and sensing devices, with restricted energy and computing capabilities, that co-operate to accomplish a large sensing task. Sensor networks can be very useful in practice. Such systems should at least guarantee the confidentiality and integrity of the information reported to the controlling authorities regarding the realization of environmental events. Therefore, key establishment is critical for the protection in wireless sensor networks and the prevention of adversaries from attacking the network. Finally in this dissertation we also propose three distributed group key establishment protocols suitable for such energy constrained networks. This dissertation is composed of two parts. Part I develops the theory of the first and second order logic of graphs - their definition, and the analysis of their properties that are expressible in the {\em first order language} of graphs. In part II we introduce some new distributed group key establishment protocols suitable for sensor networks. Several key establishment schemes are derived and their performance is demonstrated.
Abstract: In wireless sensor networks data propagation is usually
performed by sensors transmitting data towards a static control center (sink). Inspired by important applications (mostly related to ambient intelligence) and as a first step towards introducing mobility, we propose the idea of having a sink moving in the network area and collecting data from sensors. We propose four characteristic mobility patterns for the sink along with different data collection strategies. Through a detailed simulation study, we evaluate several important performance properties of each protocol. Our findings demonstrate that by taking advantage of the sink's mobility, we can significantly reduce the energy spent in relaying traffic and thus greatly extend the lifetime of the network.
Abstract: Smart Dust is a set of a ast number of ultra-small fully autonomous computing and communication devices, with very restricted energy and computing capabilities, that cooperate to quickly and efficiently accomplish a large sensing task. Smart Dust can be very useful in practice i.e. in the local detection of a remote crucial event and the propagation of data reporting its realization. In this work we make an effort towards the research on smart dust from a basic algorithmic point of view. We first provide a simple but realistic model for smart dust and present an interesting problem, which is how to propagate efficiently information on an event detected locally. Then we present smart dust protocols for local detection and propagation that are simple enough to be implemented on real smart dust systems, and perform, under some simplifying assumptions, a rigorous average case analysis of their efficiency and energy consumption (and their interplay). This analysis leads to concrete results showing that our protocols are very efficient.
Abstract: Smart Dust is a set of a vast number of ultra-small fully
autonomous computing and communication devices, with very restricted
energy and computing capabilities, that co-operate to quickly and efficiently
accomplish a large sensing task.
Smart Dust can be very useful in practice
i.e. in the local detection of a remote crucial event and
the propagation of data reporting its realization.
In this work we make an effort towards the research on smart dust
from a basic algorithmic point of view.
We first provide a simple but realistic model for smart dust
and present an interesting problem, which is how to propagate efficiently
information on an event detected locally.
Then we present smart dust protocols for local detection
and propagation that are simple enough to be implemented
on real smart dust systems, and perform, under some simplifying assumptions,
a rigorous average case analysis of their efficiency and energy consumption
(and their interplay).
This analysis leads to concrete results showing that our protocols
are very efficient.
Abstract: Buildings are among the largest consumers of electricity with a significant portion of this energy use is wasted in unoccupied areas or improperly installed devices.
Identifying such power leaks is hard especially in large office and enterprise buildings.
In this paper we present the design and implementation of a system that uses an underlying sensor network to provide accurate real time information about various characteristics like occupancy, lighting, temperature and power consumption at different levels of granularity.
All sensor devices require minimal installation and maintenance.
Using an experimental installation we evaluate a number of applications and services that achieve energy savings by applying different power conservation policies.
Furthermore we provide energy measurements to users and occupants to show how various choices and behaviors affect their personal energy savings.
Abstract: One of the most eminent problems in sensor networks is the
routing of data to a central destination in a robust and e±cient manner.
In this work we propose a new scalable protocol for propagating infor-
mation about a sensed event towards a receiving center. Using only local
information and total absence of coordination between sensors our pro-
tocol achieves to propagate the sensed data to a receiving center by ac-
tivating only those nodes that lie very close to the optimal path between
the source of the event and the destination, resulting in low activation of
the network's sensors. Thus the protocol is very energy e±cient. Further-
more, our protocol is robust as it manages to propagate the information
even when sensors fail with certain probability.
Abstract: We consider the important problem of energy balanced data propagation in wireless sensor networks and we extend and generalize
previous works by allowing adaptive energy assignment. We consider the data gathering problem where data are generated by the sensors and
must be routed toward a unique sink. Sensors route data by either sending the data directly to the sink or in a multi-hop fashion by delivering
the data to a neighbouring sensor. Direct and neighbouring transmissions require different levels of energy consumption. Basically, the protocols balance the energy consumption among the sensors by computing the adequate ratios of direct and neighbouring transmissions. An abstract model of energy dissipation as a random walk is proposed, along with rigorous performance analysis techniques. Two efficient distributed algorithms are presented and analysed, by both rigorous means and simulation.
The first one is easy to implement and fast to execute. The protocol assumes that sensors know a-priori the rate of data they generate.
The sink collects and processes all these information in order to compute the relevant value of the protocol parameter. This value is transmitted
to the sensors which individually compute their optimal ratios of direct and neighbouring transmissions. The second protocol avoids the necessary a-priori knowledge of the data rate generated by sensors by inferring the relevant information from the observation of the data paths.
Furthermore, this algorithm is based on stochastic estimation methods and is adaptive to environmental changes.
Abstract: Today˘s students are the citizens of tomorrow, and they should have the skills and tools to understand and respond to climate change. Green Awareness in Action (GAIA) has built an IoT infrastructure within 25 schools in Europe, in order to enable lectures that target sustainability and energy efficiency, based on data produced inside school buildings. The school community has reacted very positively to this approach and has reduced energy consumption as a consequence.
Abstract: A lot of activity is being devoted to studying issues related to energy consumption and efficiency in our buildings, and especially on public buildings. In this context, the educational public buildings should bean important part of the equation. At the same time, there is an evident need for open datasets, which should be publicly available for researchers to use. We have implemented a real-world multi-site Inter-net of Things (IoT) deployment, comprising 25 school buildings across Europe, primarily designed as a foundation for enabling IoT-based energy awareness and sustainability lectures and promoting data-driven energy-saving behaviors. In this work, we present some of the basic aspects to producing datasets from this deployment and discuss its potential uses. We also provide a brief discussion on data derived from a preliminary analysis of thermal comfort-related data produced from this infrastructure.
Abstract: We propose and evaluate the performance of a new MAC-layer protocol for mobile ad hoc networks, called the Slow Start Power Controlled (abbreviated SSPC) protocol. SSPC improves on IEEE 802.11 by using power control for the RTS/CTS and DATA frame transmissions, so as to reduce energy consumption and increase network throughput and lifetime. In our scheme the transmission power used for the RTS frames is not constant, but follows a slow start principle. The CTS frames, which are sent at maximum transmission power, prevent the neighbouring nodes from transmitting their DATA frames at power levels higher than a computed threshold, while allowing them to transmit at power levels less than that threshold. Reduced energy consumption is achieved by adjusting the node transmission power to the minimum required value for reliable reception at the receiving node, while increase in network throughput is achieved by allowing more transmissions to take place simultaneously. The slow start principle used for calculating the appropriate DATA frames transmission power and the possibility of more simultaneous collision-free transmissions differentiate the SSPC protocol from the other MAC solutions proposed for IEEE 802.11. Simulation results indicate that the SSPC protocol achieves a significant reduction in power consumption, average packet delay and frequency of RTS frame collisions, and a significant increase in network throughput and received-to-sent packets ratio compared to IEEE 802.11 protocol.
Abstract: The use of maker community tools and IoT technologies inside classrooms is spreading in an increasing number of education and science fields. GAIA is a European research project focused on achieving behavior change for sustainability and energy awareness in schools. In this work, we report on how a large IoT deployment in a number of educational buildings and real-world data from this infrastructure, are utilized to support a "maker" lab kit activity inside the classroom, together with a serious game. We also provide some insights to the integration of these activities in the school curriculum, along with a discussion on our feedback so far from a series of workshop activities in a number of schools. Our initial results show strong acceptance by the school community.
Abstract: The Internet of Things (IoT) and smart cities are two of the most popular directions the research community is pursuing very actively. But although we have made great progress in many fields, we are still trying to figure out how we can utilize our smart city and IoT infrastructures, in order to produce reliable, economically sustainable solutions that create public value, and even more so in the field of education.
GAIA1, a Horizon2020 EC-funded project, has developed an IoT infrastructure across school buildings in Europe. Its primary aim has been to raise awareness about energy consumption and sustainability, based on real-world sensor data produced inside the school buildings where students and teachers live and work. Today's students are the citizens of tomorrow, and they should have the skills to understand and respond to challenges like climate change. Currently, 25 educational building sites participate in GAIA, located in Sweden, Italy, and Greece. An IoT infrastructure [1] is installed in these buildings, monitoring in real-time their power consumption, as well as several indoor and outdoor environmental parameters.
Abstract: Data propagation in wireless sensor networks can be performed either by hop-by-hop single transmissions or by multi-path broadcast of data. Although several energy-aware MAC layer protocols exist that operate very well in the case of single point-to-point transmissions, none is especially designed and suitable for multiple broadcast transmissions.In this paper we propose a family of new protocols suitable of multi-path broadcast of data, and show, through a detailed and extended simulation evaluation, that our parameter-based protocols significantly reduce the number of collisions and thus increase the rate of successful message delivery (to above 90%) by trading off the average propagation delay. At the same time, our protocols are shown to be very energy efficient, in terms of the average energy dissipation per delivered message.
