Abstract: We propose a simple obstacle model to be used while simulating wireless sensor networks. To the best of our knowledge, this is the first time such an integrated and systematic obstacle model for these networks has been proposed. We define several types of obstacles that can be found inside the deployment area of a wireless sensor network and provide a categorization of these obstacles based on their nature (physical and communication obstacles, i.e. obstacles that are formed out of node distribution patterns or have physical presence, respectively), their shape and their change of nature over time. We make an eXtension to a custom-made sensor network simulator (simDust) and conduct a number of simulations in order to study the effect of obstacles on the performance of some representative (in terms of their logic) data propagation protocols for wireless sensor networks. Our findings confirm that obstacle presence has a significant impact on protocol performance, and also that different obstacle shapes and sizes may affect each protocol in different ways. This provides an insight into how a routing protocol will perform in the presence of obstacles and highlights possible protocol shortcomings. Moreover, our results show that the effect of obstacles is not directly related to the density of a sensor network, and cannot be emulated only by changing the network density.
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: Wireless Sensor Networks are by nature highly dynamic and communication between sensors is completely ad hoc, especially when mobile devices are part of the setup. Numerous protocols and applications proposed for such networks
operate on the assumption that knowledge of the neighborhood is a priori available to all nodes. As a result, WSN deployments need to use or implement from scratch a neighborhood discovery mechanism. In this work we present a new protocol based on adaptive periodic beacon exchanges. We totally avoid continuous beaconing by adjusting the rate of broadcasts using the concept of consistency over the understanding of neighborhood that nearby devices share. We propose, implement and evaluate our adaptive neighborhood discovery protocol over our experimental testbed and using large scale simulations. Our results indicate that the
new protocol operates more eciently than existing reference implementations while it provides valid information to applications that use it. Extensive performance evaluation indicates that it successfully reduces generated network traffic by 90% and increases network lifetime by 20% compared to existing mechanisms that rely on continuous beaconing.
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: Smart cities are becoming a vibrant application domain for a number of science fields. As such, service providers and stakeholders are beginning to integrate co-creation aspects into current implementations to shape the future smart city solutions. In this context, holistic solutions are required to test such aspects in real city-scale IoT deployments, considering the complex city ecosystems. In this work, we discuss OrganiCity¢s implementation of an Experimentation-as-a-Service framework, presenting a toolset that allows developing, deploying and evaluating smart city solutions in a one-stop shop manner. This is the first time such an integrated toolset is offered in the context of a large-scale IoT infrastructure, which spans across multiple European cities. We discuss the design and implementation of the toolset, presenting our view on what Experimentation-as-a-Service should provide, and how it is implemented. We present initial feedback from 25 experimenter teams that have utilized this toolset in the OrganiCity project, along with a discussion on two detailed actual use cases to validate our approach. Learnings from all experiments are discussed as well as architectural considerations for platform scaling. Our feedback from experimenters indicates that Experimentation-as-a-Service is a viable and useful approach.
Abstract: In this paper we study the problem of basic communication
in ad-hoc mobile networks where the deployment area changes in a
highly dynamic way and is unknown. We call such networks
highly changing ad-hoc mobile networks.
For such networks we investigate an efficient communication protocol which extends
the idea (introduced in [WAE01,POMC01]) of exploiting the co-ordinated
motion of a small part of an ad-hoc mobile
network (the ``runners support") to achieve
very fast communication between any two mobile users of the network.
The basic idea of the new protocol presented here is, instead
of using a fixed sized support for the whole duration of the protocol,
to employ a support of some initial (small) size which
adapts (given some time which can be made fast enough) to the
actual levels of traffic and the
(unknown and possibly rapidly changing) network area by
changing its size in order to converge to an optimal size,
thus satisfying certain Quality of Service criteria.
We provide here some proofs of correctness and fault tolerance
of this adaptive approach and we also provide analytical results
using Markov Chains and random walk techniques to show that such
an adaptive approach is, for this class of ad-hoc mobile networks, significantly more efficient than a simple non-adaptive
implementation of the basic ``runners support" idea.
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: 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: We investigate the problem of communication in an ad-hoc mobile network, that is, we assume the extreme case of a total absense of any fixed network infrastructure (for example a case of rapid deployment of a set of mobile hosts in an unknown terrain). We propose, in such a case, that a small subset of the deployed hosts (which we call the support) should be used for network operations. However, the vast majority of the hosts are moving arbitrarily according to application needs.
We then provide a simple, correct and efficient protocol for communication that avoids message flooding. Our protocol manages to establish communication between any pair of mobile hosts in small, a-priori guaranteed expected time bounds even in the worst case of arbitrary motions of the hosts that not in the support (provided that they do not deliberately try to avoid the support). These time bounds, interestingly, do not depend, on the number of mobile hosts that do not belong in the support. They depend only on the size of the area of motions. Our protocol can be implemented in very efficient ways by exploiting knowledge of the space of motions or by adding more power to the hosts of the support.
Our results exploit and further develop some fundamental properties of random walks in finite graphs.
Abstract: We present the conceptual basis and the initial planning for an open source management architecture for wireless sensor networks (WSN). Although there is an abundance of open source tools serving the administrative needs of WSN deployments, there is a lack of tools or platforms for high level integrated WSN management. This is because of a variety of factors, including the lack of open source management tools, the immaturity of tools that offer manageability for WSNs, the limited high level management capabilities of sensor devices and architectures, and the lack of standardization. The current work is, to our knowledge, the first effort to conceptualize, formalize and design a remote, integrated management platform for the support of WSN research laboratories. The platform is based on the integration and extension of two innovative platforms: jWebDust, a WSN operation and management platform, and OpenRSM, an open source integrated remote systems and network management platform. The proposed system architecture can support several levels of integration (infrastructure management, functionality integration, firmware management), corresponding to different use-cases and application settings.
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: Counting in general, and estimating the cardinality of (multi-) sets in particular, is highly desirable for a large variety of applications, representing a foundational block for the efficient deployment and access of emerging internet-scale information systems. Examples of such applications range from optimizing query access plans in internet-scale databases, to evaluating the significance (rank/score) of various data items in information retrieval applications. The key constraints that any acceptable solution must satisfy are: (i) efficiency: the number of nodes that need be contacted for counting purposes must be small in order to enjoy small latency and bandwidth requirements; (ii) scalability, seemingly contradicting the efficiency goal: arbitrarily large numbers of nodes nay need to add elements to a (multi-) set, which dictates the need for a highly distributed solution, avoiding server-based scalability, bottleneck, and availability problems; (iii) access and storage load balancing: counting and related overhead chores should be distributed fairly to the nodes of the network; (iv) accuracy: tunable, robust (in the presence of dynamics and failures) and highly accurate cardinality estimation; (v) simplicity and ease of integration: special, solution-specific indexing structures should be avoided. In this paper, first we contribute a highly-distributed, scalable, efficient, and accurate (multi-) set cardinality estimator. Subsequently, we show how to use our solution to build and maintain histograms, which have been a basic building block for query optimization for centralized databases, facilitating their porting into the realm of internet-scale data networks.
Abstract: The purpose of the first Student Workshop on Wireless Sensor Networks is to bring together both graduate and undergraduate students working in the area of wireless sensor networks, with focus on applications, real-world experiments or deployments of wireless sensor networks. Students will have the opportunity to interact with their peers and publicize and get feedback on their work, exchange experiences, make contacts, and learn what other students are doing in the Wireless Sensor Networks area. The workshop would be a day-long program organized in such a way to promote lively discussions.
Abstract: The Greek School Network (GSN) is the nationwide network that connects all units of primary and secondary education in Greece. GSN offers a significant set of diverse services to more than 15.000 schools and administrative units, and more than 60.000 teachers, placing GSN second in infrastructure size nationwide. GSN has relied on the emerging power of open source software to build cutting-edge services capable of covering internal administrative and monitoring needs, end user demands, and, foremost, modern pedagogical requirements for tools and services. GSN provides a wide set of advanced services, varying from web mail to virtual classrooms and synchronous/asynchronous tele-education. This paper presents an evaluation of GSN open source services based on the opinions of users who use GSN for educational purposes, and on usage and traffic measurement statistics. The paper reaches the conclusion that open source software provides a sound technological platform that meets the needs for cutting edge educational services deployment, and innovative, competitive software production for educational networks.
Abstract: In this work we introduce two practical and interesting models of ad-hoc mobile networks: (a) hierarchical ad-hoc networks, comprised of dense subnetworks of mobile users interconnected by a very fast yet limited backbone infrastructure, (b) highly changing ad-hoc networks, where the deployment area changes in a highly dynamic way and is unknown to the protocol. In such networks, we study the problem of basic communication, i.e., sending messages from a sender node to a receiver node. For highly changing networks, we investigate an efficient communication protocol exploiting the coordinated motion of a small part of an ad-hoc mobile network (the ldquorunners supportrdquo) to achieve fast communication. This protocol instead of using a fixed sized support for the whole duration of the protocol, employs a support of some initial (small) size which adapts (given some time which can be made fast enough) to the actual levels of traffic and the (unknown and possibly rapidly changing) network area, by changing its size in order to converge to an optimal size, thus satisfying certain Quality of Service criteria. Using random walks theory, we show that such an adaptive approach is, for this class of ad-hoc mobile networks, significantly more efficient than a simple non-adaptive implementation of the basic ldquorunners supportrdquo idea, introduced in [9,10]. For hierarchical ad-hoc networks, we establish communication by using a ldquorunnersrdquo support in each lower level of the hierarchy (i.e., in each dense subnetwork), while the fast backbone provides interconnections at the upper level (i.e., between the various subnetworks). We analyze the time efficiency of this hierarchical approach. This analysis indicates that the hierarchical implementation of the support approach significantly outperforms a simple implementation of it in hierarchical ad-hoc networks. Finally, we discuss a possible combination of the two approaches above (the hierarchical and the adaptive ones) that can be useful in ad-hoc networks that are both hierarchical and highly changing. Indeed, in such cases the hierarchical nature of these networks further supports the possibility of adaptation.
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 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 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 study the problem of localizing and tracking multiple moving targets in wireless sensor
networks, from a network design perspective i.e. towards estimating the least possible number
of sensors to be deployed, their positions and operation chatacteristics needed to perform the
tracking task. To avoid an expensive massive deployment, we try to take advantage of
possible coverage ovelaps 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 combinatorial
problem of covering a universe of elements by at least three sets (to ensure that each point in
the network area is covered at any time by at least three sensors, and thus being localized). We
then design and analyze an efficient approximate method for sensor placement and operation,
that with high probability and in polynomial expected time achieves a (log n) approximation
ratio to the optimal solution. Our network design solution can be combined with alternative
collaborative processing methods, to suitably fit different tracking scenaria.
Abstract: We study the problem of localizing and tracking multiple moving targets in wireless sensor networks, from a network design perspective i.e. towards estimating the least possible number of sensors to be deployed, their positions and operation characteristics needed to 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 combinatorial problem of covering a universe of elements by at least three sets (to ensure that each point in the network area is covered at any time by at least three sensors, and thus being localized). We then design and analyze an efficient approximate method for sensor placement and operation, that with high probability and in polynomial expected time achieves a {\`E}(logn) approximation ratio to the optimal solution. Our network design solution can be combined with alternative collaborative processing methods, to suitably fit different tracking scenarios.
Abstract: Urban ecosystems are becoming one of the most potentially attractive scenarios for innovating new services and technologies. In parallel, city managers, urban utilities and other stakeholders are fostering the intensive use of advanced technologies aiming at improving present city performance and its sustainability. The deployment of such technology entails the generation of massive amounts of information which in many cases might become useful for other services and applications. Hence, aiming at taking advantage of such massive amounts of information and deployed technology as well as breaking the potential digital barrier that can be raised, some easy-to-use tools have to be made available to the urban stakeholders. These tools integrated in a platform, operated directly or indirectly by the city, provides a singular opportunity for exploiting the concept of connected city whilst fostering innovation in all city dimensions and making the co-creation concept a reality and eventually impacting on government policies.
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: 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: Core optical networks using reconfigurable optical
switches and tunable lasers appear to be on the road towards
widespread deployment and could evolve to all-optical mesh
networks in the coming future. Considering the impact of physical
layer impairments in the planning and operation of all-optical
(and translucent) networks is the main focus of the DICONET
project. The impairment aware network planning and operation
tool (NPOT) is the main outcome of DICONET project, which
is explained in detail in this paper. The key building blocks of
the NPOT, consisting of network description repositories, the
physical layer performance evaluator, the impairment aware
routing and wavelength assignment engines, the component
placement modules, failure handling and the integration of
NPOT in the control plane are the main contributions of this
work. Besides, the experimental result of DICONET proposal for
centralized and distributed control plane integration schemes and
the performance of the failure handling in terms of restoration
time is presented in this work.
Abstract: Online and Realtime counting and estimating the cardinality of sets is highly desirable for a large variety of applications, representing a foundational block for the efficient deployment and access of emerging internet scale information systems. In this work we implement three well known duplicate
insensitive counting algorithms and evaluate their performance in a testbed of resource-limited commercial off-the-shelf hardware devices. We focus on devices that can be used in wireless mobile and sensor applications and evaluate the memory complexity, time complexity and absolute error of the algorithms under different realistic scenaria. Our findings indicate the suitability of each algorithm depending on the application characteristics.
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: 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: Human mobility monitoring and respective traces are important for understanding human behavior, respective patterns and associated context. Such data can be potentially used in business intelligence-oriented systems, for providing added value commercial services or insight to internal enterprise procedures. At the same time, smartphones are rapidly becoming an indispensable tool for our everyday life, while their advanced networking and computing capabilities are increasingly being used as enablers for new applications. We discuss here a system using a stable computing and networking infrastructure along with smartphone applications, based on commodity technologies, meant to be deployed rapidly and provide analytics almost in real-time for such aspects. We also discuss a related scenario in order to provide insight as to where our system could be used. We briefly present the deployment of our system in two settings, an office building and a research exhibition event, along with our experiences. Our findings show that it is feasible and efficient to deploy and operate our system relatively easy, producing meaningful data.
Abstract: Abstract— Numerous smart city testbeds and system deployments have surfaced around the world, aiming to provide services over unified large heterogeneous IoT infrastructures. Although we have achieved new scales in smart city installations and systems, so far the focus has been to provide diverse sources of data to smart city services consumers, while neglecting to provide ways to simplify making good use of them. We believe that knowledge creation in smart cities through data annotation, supported in both an automated and a crowdsourced manner, is an aspect that will bring additional value to smart cities. We present here our approach, aiming to utilize an existing smart city deployment and the OrganiCity software ecosystem. We discuss key challenges along with characteristic use cases, and report on our design and implementation, along with preliminary results.
Abstract: Although we have reached new levels in smart city installations and systems, efforts so far have focused on providing diverse sources of data to smart city services consumers while neglecting to provide ways to simplify making good use of them. In this context, one first step that will bring added value to smart cities is knowledge creation in smart cities through anomaly detection and data annotation, supported in both an automated and a crowdsourced manner. We present here LearningCity, our solution that has been validated over an existing smart city deployment in Santander, and the OrganiCity experimentation-as-a-service ecosystem. We discuss key challenges along with characteristic use cases, and report on our design and implementation, together with some preliminary results derived from combining large smart city datasets with machine learning.
Abstract: Internet of Things technologies are considered the next big
step in Smart Building installations. Although such technologies have
been widely studied in simulation and experimental scenarios it is not so
obvious how problems of real world installations should be dealt with. In
this work we deploy IoT devices for sensing and control in a multi-office
space and employ technologies such as CoAP, RESTful interfaces and
Semantic Descriptions to integrate them with the Web. We report our
research goals, the challenges we faced, the decisions we made and the
experience gained from the design, deployment and operation of all the
hardware and software components that compose our system.
Abstract: In this work, we propose an obstacle model to be used while simulating wireless sensor networks. To the best of our knowledge, this is the first time such an integrated and systematic obstacle model appears. We define several types of obstacles that can be found inside the deployment area of a wireless sensor network and provide a categorization of these obstacles, based on their nature (physical and communication obstacles), their shape, as well as
their nature to change over time. In light of this obstacle model we conduct extensive simulations in order to study the effects of obstacles on the performance of representative data propagation protocols for wireless sensor networks. Our findings
show that obstacle presence has a significant impact on protocol performance. Also, we demonstrate the effect of each obstacle type on different protocols, thus providing the network designer with advice on which protocol is best to use.
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 work, we explore context-aware application scenarios that become possible utilizing semantically-rich information derived from real-world mobility and presence traces. Traces produced by people carrying personal mobile devices, capturing social and contextual interactions, serve as enables for Future Internet applications. We discuss the fundamental concepts, technical issues and related research challenges. We propose a reference architecture for setting up a system that collects such traces in a Smart City environment. We present the algorithms used to process the traces and infer interactions and interests for the observed populations. We conduct two 3-day trial deployments: one in an office environment and the other in the context of a Smart Conference application. We discuss our findings regarding the system's capability to track interactions and the overall efficacy of the application.
Abstract: — This work discusses PatrasSense, a system utilizing a range of technologies for monitoring environmental conditions, based on the concept of participatory monitoring. We discuss here the main issues in this category of applications, and its relation to the Real World Internet vision. We are interested in the use of sensors for collecting data related to the quality of life in urban areas, making it publicly available. We describe a possible architecture for such a system and a plan for deployment in the city of Patras, Greece. We have thus far implemented a set of features and conducted an initial set of small-scale experiments using sensor devices mounted on vehicles. We report on the respective results
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: 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: 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: Embedded computing devices dominate our everyday activities, from cell phones to wireless sensors that collect and process data for various applications. Although desktop and high-end server security seems to be under control by the use of current security technology, securing the low-end embedded computing systems is a difficult long-term problem. This is mainly due to the fact that the embedded systems are constrained by their operational environment and the limited resources they are equipped with. Recent research activities focus on the deployment of lightweight cryptographic algorithms and security protocols that are well suited to the limited resources of low-end embedded systems. Elliptic Curve Cryptography (ECC) offers an interesting alternative to the classical public key cryptography for embedded systems (e.g., RSA and ElGamal), since it uses smaller key sizes for achieving the same security level, thus making ECC an attractive and efficient alternative for deployment in embedded systems. In this chapter, the processing requirements and architectures for secure network access, communication functions, storage, and high availability of embedded devices are discussed. In addition, ECC-based state-of-the-art lightweight cryptographic primitives for the deployment of security protocols in embedded systems that fulfill the requirements are presented.
Abstract: We investigate here the problem
of establishing communication in an ad-hoc
mobile network, that is, we assume the extreme case
of a total absence of any fixed network infrastructure
(for example a case of rapid deployment of a set of
mobile hosts in an unknown terrain). We propose, in
such a case, that a small
subset of the deployed hosts (which we call the support)
should be used to manage network operations.
However, the vast majority
of the hosts are moving arbitrarily according
to application needs.
We then provide a simple, correct and efficient protocol
for communication establishment
that avoids message flooding.
Our protocol manages to establish communication between
any pair of mobile hosts in small, a-priori
guaranteed time bounds even in the worst case of arbitrary motions of the hosts that do not belong to
the support (provided that they do not deliberately try
to avoid the support).
These time bounds, interestingly, do not depend,
on the number of mobile hosts that do not
belong in the support. They depend only on the size of the area
of motions.
Our protocol can be implemented
in very efficient ways by exploiting knowledge of the space of motions
or by adding more power to the hosts of the support.
Our results exploit and further develop some
fundamental properties of random walks in finite graphs.
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 present the conceptual basis and the initial planning for an open
source management architecture for wireless sensor networks (WSN). Although
there is an abundance of open source tools serving the administrative needs of
WSN deployments, there is a lack of tools or platforms for high level integrated
WSN management. The current work is, to our knowledge, the first effort to
conceptualize and design a remote, integrated management platform for the
support of WSN research laboratories. The platform is based on the integration
and extension of two innovative platforms: jWebDust, a WSN operation and
management platform, and OpenRSM, an open source integrated remote
systems and network management platform. The proposed system architecture
can support several levels of integration in order to cover to multiple,
qualitatively differentiated use-cases.
Abstract: Advancements in both on-board and wireless communication technologies provide the necessary backbone for the deployment of a network between vehicles. Most of the envisioned applications for these networks would be greatly favored by multimedia support provisioning. However, there are several issues to be handled in order to provide multimedia services with reasonable quality. In this work, we analyze a specific multimedia service that can be used by several interesting applications: video broadcasting. Particularly, we throughly discuss and evaluate the role of redundancy in improving this service. We have verified that although redundancy does increase the effectiveness in video broadcasting, coding techniques do not improve redundancy's efficiency.
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: Recent activity in the field of Internet-of-Things experimentation has focused on the federation of discrete testbeds, thus placing less effort in the integration of other related technologies, such as smartphones; also, while it is gradually moving to more application-oriented paths, such as urban settings, it has not dealt in large with applications having social networking features. We argue here that current IoT infrastructure, testbeds and related software technologies should be used in such a context, capturing real-world human mobility and social networking interactions, for use in evaluating and fine-tuning realistic mobility models and designing human-centric applications. We discuss a system for producing traces for a new generation of human-centric applications, utilizing technologies such as Bluetooth and focusing on human interactions. We describe the architecture for this system and the respective implementation details presenting two distinct deployments; one in an office environment and another in an exhibition/conference event (FET'11, The European Future Technologies Conference and Exhibition) with 103 active participants combined, thus covering two popular scenarios for human centric applications. Our system provides online, almost real-time, feedback and statistics and its implementation allows for rapid and robust deployment, utilizing mainstream technologies and components.
