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: eVoting is considered to be one of the most challenging domains of modern eGovernment and one of the main vehicles for increasing eParticipation among citizens. One of the main obstacles for its wide adoptionis the reluctance of citizens to participate in electronic voting procedures. This reluctance can be partially attributed to the low penetration of technology among citizens. However, the main reason behind this reluctance is the lack of trust which stems from the belief of citizens that systems implementing an eVoting process will violate their privacy. The departure point of this approach is that the emergence of such a belief can be considerably facilitated by designing and building systems in a way that evidence about the system’s properties is produced during the design process. In this way, the designers can demonstrate the respect in privacy using this evidence that can be understood and checked by the specialist and the informed layman. These tools and models should provide sufficient evidence that the target system handles privacy concerns and requirements that can remove enough of the fears towards eVoting. This paper presents the efforts of the authors‘ organization, the Computer Technology Institute and Press “Diophantus” (CTI), towards the design and implementation of an eVoting system, called PNYKA, with demonstrable security properties. This system was based on a trust-centered engineering approach for building general security critical systems. The authors‘ approach is pragmatic rather than theoretical in that it sidesteps the controversy that besets the nature of trust in information systems and starts with a working definition of trust as people’s positive attitude towards a system that transparently and demonstrably performs its operations, respecting their privacy. The authors also discuss the social side of eVoting, i.e. how one can help boost its acceptance by large social groups targeting the whole population of the country. The authors view eVoting as an innovation that must be diffused to a population and then employ a theoretical model that studies diffusion of innovation in social network, delineating structural properties of the network that help diffuse the innovation fast. Furthermore, the authors explain how CTI’s current situation empowers CTI to realize its vision to implement a privacy preserving, discussion and public consultation forum in Greece. This forum will link, together, all Greek educational institutes in order to provide a privacy preserving discussion and opinion gathering tool useful in decision making within the Greek educational system.
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: 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: The problem of communication among mobile nodes is one of the most fundamental problems in ad hoc mobile networks and is at the core of many algorithms, such as for counting the number of nodes, electing a leader, data processing etc. For an exposition of several important problems in ad hoc mobile networks. The work of Chatzigiannakis, Nikoletseas and Spirakis focuses on wireless mobile networks that are subject to highly dynamic structural changes created by mobility, channel fluctuations and device failures. These changes affect topological connectivity, occur with high frequency and may not be predictable in advance. Therefore, the environment where the nodes move (in three-dimensional space with possible obstacles) as well as the motion that the nodes perform are \textit{input} to any distributed algorithm.
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: This paper deals with early obstacles recognition in wireless sensor networks under various traffic
patterns. In the presence of obstacles, the efficiency of routing algorithms is increased by voluntarily avoiding some regions in the vicinity of obstacles, areas which we call dead-ends. In this paper, we first propose a fast convergent routing algorithm with proactive dead-end detection together with a formal definition and description of dead-ends. Secondly, we present a generalization of this algorithm which improves performances in all to many and all to all traffic patterns. In a third part we prove that this algorithm produces paths that are optimal up to a
constant factor of 2ð+1. In a fourth part we consider the reactive version of the algorithm which is an extension of a previously known early obstacle detection algorithm. Finally we give experimental results to illustrate the efficiency of our algorithms in different scenarios.
Abstract: ManyWSN algorithms and applications are based on knowledge
regarding the position of nodes inside the network area.
However, the solution of using GPS based modules in order
to perform localization in WSNs is a rather expensive solution
and in the case of indoor applications, such as smart
buildings, is also not applicable. Therefore, several techniques
have been studied in order to perform relative localization
in WSNs; that is, to compute the position of
a node inside the network area relatively to the position
of other nodes. Many such techniques are based on indicators
like the Radio Signal Strength Indicator (RSSI)
and the Link Quality Indicator (LQI). These techniques are
based on the assumption that there is strong correlation between
the Euclidian distance of the communicating motes
and these indicators. Therefore, high values of RSSI and
LQI should indicate physical proximity of two communicating
nodes. However, these indicators do not depend solely on
distance. Physical obstacles, ambient electromagnetic noise
and interferences from other wireless transmissions also affect
the quality of wireless communication in a stochastic
way. In this paper we propose, implement, experimentally
fine tune and evaluate a localization algorithm that exploits
the stochastic nature of interferences during wireless communications
in order to perform localization in WSNs. Our
algorithm is particularly designed for in-door localisation of
moving people in smart buildings. The localisation achieved
is fine-grained, i.e. the position of the target mote is successfully
computed with approximately one meter accuracy.
This fine-grained localisation can be used by smart Building
Management Systems in many applications such as room
adaptation to presence. In our scenario, our proposed algorithm is used by a smart room in order to localise the
position of people inside the room and adapt room illumination
accordingly.
Abstract: Geographic routing is becoming the protocol of choice for many sensor network applications. Some very efficient geographic routing algorithms exist, however they require a preliminary planarization of the communication graph. Planarization induces overhead which makes this approach not optimal when lightweight protocols are required. On the other hand, georouting algorithms which do not rely on planarization have fairly low success rates and either fail to route messages around all but the simplest obstacles or have a high topology control overhead (e.g. contour detection algorithms). In this entry we describe the GRIC algorithm which was designed to overcome some of those limitations. The GRIC algorithm was proposed in [PN07a]. It is the first lightweight and efficient on demand (i.e. all-to-all) geographic routing algorithm which does not require planarization, has almost 100% delivery rates (when no obstacles are added), and behaves well in the presence of large communication blocking obstacles.
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: We propose local mechanisms for efficiently marking the broader network region around obstacles, for data propagation to early enough avoid them towards near-optimal routing paths. In particular, our methods perform an online identification of sensors lying near obstacle boundaries,which then appropriately emit beacon messages in the network towards establishing efficient obstacle avoidance paths. We provide a variety of beacon dissemination schemes that satisfy different trade-offs between protocol overhead and performance. Compared to greedy, face routing and trustbased methods in the state of the art, our methods achieve significantly shorter propagation paths, while introducing much lower overhead and converging faster to near-optimality.
Abstract: We propose local mechanisms for efficiently marking the
broader network region around obstacles, for data propagation
to early enough avoid them towards near-optimal
routing paths. In particular, our methods perform an online
identification of sensors lying near obstacle boundaries,
which then appropriately emit beacon messages in the network
towards establishing efficient obstacle avoidance paths.
We provide a variety of beacon dissemination schemes that
satisfy different trade-offs between protocol overhead and
performance. Compared to greedy, face routing and trustbased
methods in the state of the art, our methods achieve
significantly shorter propagation paths, while introducing
much lower overhead and converging faster to near-optimality.
Abstract: Wireless sensor networks are about to be part of everyday life. Homes and workplaces capable of self-controlling and adapting air-conditioning for different temperature and humidity levels, sleepless forests ready to detect and react in case of a fire, vehicles able to avoid sudden obstacles or possibly able to self-organize routes to avoid congestion, and so on, will probably be commonplace in the very near future. Mobility plays a central role in such systems and so does passive mobility, that is, mobility of the network stemming from the environment itself. The population protocol model was an intellectual invention aiming to describe such systems in a minimalistic and analysis-friendly way. Having as a starting-point the inherent limitations but also the fundamental establishments of the population protocol model, we try in this monograph to present some realistic and practical enhancements that give birth to some new and surprisingly powerful (for this kind of systems) computational models.
Abstract: Geographic routing is becoming the protocol of choice for
many sensor network applications. The current state of the art is unsatisfactory:
some algorithms are very efficient, however they require a
preliminary planarization of the communication graph. Planarization induces
overhead and is thus not realistic for some scenarios such as the
case of highly dynamic network topologies. On the other hand, georouting
algorithms which do not rely on planarization have fairly low success
rates and fail to route messages around all but the simplest obstacles.
To overcome these limitations, we propose the GRIC geographic routing
algorithm. It has absolutely no topology maintenance overhead, almost
100% delivery rates (when no obstacles are added), bypasses large convex
obstacles, finds short paths to the destination, resists link failure
and is fairly simple to implement. The case of hard concave obstacles
is also studied; such obstacles are hard instances for which performance
diminishes.
Abstract: For the Internet of Things to finally become a reality, obstacles on different levels need to be overcome. This is especially true for the upcoming challenge of leaving the domain of technical experts and scientists. Devices need to connect to the Internet and be able to offer services. They have to announce and describe these services in machine understandable ways so that user-facing systems are able to find and utilize them. They have to learn about their physical surroundings, so that they can serve sensing or acting purposes without explicit configuration or programming. Finally, it must be possible to include IoT devices in complex systems that combine local and remote data, from different sources, in novel and surprising ways.
We show how all of that is possible today. Our solution uses open standards and state-of-the art protocols to achieve this. It is based on 6LowPAN and CoAP for the communications part, semantic web technologies for meaningful data exchange, autonomous sensor correlation to learn about the environment, and software built around the Linked Data principles to be open for novel and unforeseen applications.