Sinks Mobility Strategy in IPv6-based WSNs for Network Lifetime Improvement

International audienceThis paper investigates the sinks mobility in IPv6- based wireless sensors networks and specially in the new IETF proposed protocol RPL (Routing Protocol for Low power and Lossy Networks). We also show that even the mobility of sinks is not an explicit design criteria, the use of mobile sinks improves the network lifetime. In this work, we propose a new distributed and weighted moving strategy for sinks in RPL. We compared our proposed mobility approach with different others strategies. The results show that our proposed mobility approach notably balances the network load which leads to a significant network lifetime gain in large scale network

Exploiting Addresses Correlation to Maximize Lifetime of IPv6 Cluster-based WSNs

International audienceImproving the network lifetime is an important design criterion for wireless sensor networks. To achieve this goal, we propose in this paper a novel approach which applies source-coding on addresses in heterogeneous IPv6 Cluster-based wireless sensor network. We formulate the problem of maximiz- ing the network lifetime when Slepian-wolf coding is applied on addresses in network composed of line-powered and battery- powered sensors. This problem optimizes the placement of line- powered sensors to enable the battery-powered ones to exploit the addresses correlation and reduce the size of their emitted packets and thus improve the network lifetime. The numerical results show that a significant network lifetime improvement can be achieved (about 25% in typical scenario)

Stratégie de Placement des Puits Mobiles dans les Réseaux de Capteurs sans Fil pour Bâtiments

National audienceLe besoin des réseaux de capteurs sans fil croit très rapidement dans un large éventail d'applications industrielles. Parmi celles-ci se trouve l'observation, le suivi des données physiques et l'automatisation des bâtiments. Dans ces réseaux, un grand nombre de capteurs transmettent via multi sauts les données collectées vers le puits le plus proche. Les capteurs qui sont proches des puits épuisent leurs réserves d'énergie beaucoup plus rapidement que les capteurs distants car ils ont une charge de trafic très importante. Ceci est dû au fait qu'ils transmettent leurs propres données ainsi que les données des capteurs éloignés provoquant ainsi prématurément la fin de la durée de vie du réseau. Le déplacement périodique des puits permet de résoudre ce problème en distribuant la charge du trafic entre les capteurs et améliorer ainsi la durée de vie du réseau. Dans ce travail, nous proposons un nouvel algorithme qui détermine le positionnement de plusieurs puits mobiles dans un réseau large échelle afin d'augmenter la durée de vie du réseau. Son principe se base sur le déplacement régulier des puits vers les capteurs distants qui ont le plus grand nombre de sauts à faire pour atteindre le puits le plus proche. Nous avons évalué les performances de notre solution par des simulations et comparé avec d'autres stratégies. Les résultats montrent que notre solution améliore considérablement la durée de vie du réseau et équilibre notablement la consommation d'énergie entre les nœuds. Ces résultats sont très utiles pour le déploiement réel de réseaux de capteurs sans fil au sein des bâtiments

Multiple Mobile Sinks Positioning in Wireless Sensor Networks for Buildings

Best Paper AwardInternational audienceReal deployment of wireless sensor networks inside build- ings is a very challenging. In fact, in such networks, a large number of small sensor devices suffer from limited energy supply. These sensors have to observe and monitor their in-door environment, and then to report the data collected to a nearest information collector, referred to as the sink node. Sensor nodes which are far away from the sink relay their data via multiple hops to reach the sink. This way of communication makes the sensors near the sink deplete their energy much faster than distant nodes because they carry heavier traffic. So what is known as a hole appears around the sink and prevents distant nodes to send their data. Consequently the network lifetime ends prematurely. One efficient solution for this problem is to relocate sinks. In this work, we aim to find the best way to relocate sinks by determining their optimal locations and the duration of their sojourn time. So, we propose an Integer Linear Programming for multiple mobile sinks which directly maximizes the network lifetime instead of minimizing the energy consumption or maximizing the residual energy, which is what was done in previous solutions. Simulations results show that with our solution, the network lifetime is extended and the energy depletion is more balanced among the nodes. We also show that relocating mobile sinks inside a whole network is more efficient than relocating mobile sinks inside different clusters and we can achieve almost 52 % network lifetime improvement in our experiments

Accurate Graph Filtering in Wireless Sensor Networks

Wireless sensor networks (WSNs) are considered as a major technology enabling the Internet of Things (IoT) paradigm. The recent emerging Graph Signal Processing field can also contribute to enabling the IoT by providing key tools, such as graph filters, for processing the data associated with the sensor devices. Graph filters can be performed over WSNs in a distributed manner by means of a certain number of communication exchanges among the nodes. But, WSNs are often affected by interferences and noise, which leads to view these networks as directed, random and time-varying graph topologies. Most of existing works neglect this problem by considering an unrealistic assumption that claims the same probability of link activation in both directions when sending a packet between two neighboring nodes. This work focuses on the problem of operating graph filtering in random asymmetric WSNs. We show first that graph filtering with finite impulse response graph filters (node-invariant and node-variant) requires having equal connectivity probabilities for all the links in order to have an unbiased filtering, which can not be achieved in practice in random WSNs. After this, we characterize the graph filtering error and present an efficient strategy to conduct graph filtering tasks over random WSNs with node-variant graph filters by maximizing accuracy, that is, ensuring a small bias-variance trade-off. In order to enforce the desired accuracy, we optimize the filter coefficients and design a cross-layer distributed scheduling algorithm at the MAC layer. Extensive numerical experiments are presented to show the efficiency of the proposed solution as well as the cross-layer distributed scheduling algorithm for the denoising application.Comment: 15 pages, 8 figures, submitted to IEEE Internet of Things Journa

Quantization in Graph Convolutional Neural Networks

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Simulation of the RPL Routing Protocol for IPv6 Sensor Networks: two cases studies

International audienceThe routing protocol for low power and lossy networks (RPL) was recently designed in the ROLL working group at IETF. Few simulation tools exist that enable its evaluation in order to prepare for its real deployment. In this paper, we provide a new evaluation of this protocol with two approaches using two different simulators adapted to our needs. We first evaluated the value of mobile sinks in wireless sensor networks to extend the network lifetime using a sensor network simulator, WSNet, augmented by our own RPL module. We then focus on the performance comparison of simulated sensor networks and real powerline communication networks (PLC) using the RPL capable COOJA simulator augmented by our own PLC module. In each case, we justify the simulator choice, describe the tools implemented and present the obtained results. Our studies give two new RPL evaluations and show the interest of choosing a simulation tool adapted to the targeted study with the associated software developments. As a conclusion, we demonstrated how these two case studies can be combined in a heterogeneous network architecture to extend its global lifetime

Towards an Efficient Positioning of Mobile Sinks in Wireless Sensor Networks inside Buildings

International audienceRecent years have witnessed an increasing need for wireless sensor networks in a wide range of applications specially for buildings automation. In such networks, many sensor nodes relay the sensed data hop by hop towards the nearest sink. The sensors closest to the sinks drain their energy much faster than distant nodes because they carry heavier traffic which causes prematurely the end of the network lifetime. Relocating the sinks can solve this problem by distributing the high traffic load among the sensors and increase the network lifetime. In this work, we propose a new scalable multi-sink heuristic algorithm (Hop) which regularly moves the sinks towards the distant nodes. We evaluated the performance of our solution by simulations and compared it with others schemes. The results show that it extends significantly the network lifetime and balances notably the energy consumption among the nodes. Such results can provide useful guidelines for real sensor network deployment

Heterogeneous IPv6 Infrastructure for Smart Energy Efficient Building

International audienceIn the context of increasing developments of home, building and city automation, the Power Line Communication (PLC) networking medium is called for unpreceeding usage. Our view of the future building networking infrastructure places PLC as the central point. We show in this paper that even if Wireless Sensors Networks (WSN) are good candidates in several cases of the sensor and actuator networking infrastructure, PLC is mandatory in several place of the smart-grid metering and command infrastructure. Also PLC will serve the infrastructure on the sensor/actuator side when the energy requirement cannot be fulfilled by autonomous battery and capacitor based nodes. PLC may provide the numerous bridges necessary to sustain a long lifetime (years) for the WSN infrastructures. This new role of PLC networking will be possible only if the inter-operability between all media and technology is made possible. Thanks to the design of converging IPv6 networking layers, we show that full inter-operability is already possible even in very tiny constrained networking devices. Moreover, low energy PLC, will be able to provide smart grid monitoring without impacting the overall energy balance

Quantization Analysis and Robust Design for Distributed Graph Filters

Distributed graph filters have found applications in wireless sensor networks (WSNs) to solve distributed tasks such as consensus, signal denoising, and reconstruction. However, when employed over WSN, the graph filters should deal with the network limited energy, processing, and communication capabilities. Quantization plays a fundamental role to improve the latter but its effects on distributed graph filtering are little understood. WSNs are also prone to random link losses due to noise and interference. The filter output is affected by both the quantization error and the topological randomness error, which, if it is not properly accounted in the filter design phase, may lead to an accumulated error through the filtering iterations and significantly degrade the performance. In this paper, we analyze how quantization affects distributed graph filtering over both time-invariant and time-varying graphs. We bring insights on the quantization effects for the two most common graph filters: the finite impulse response (FIR) and autoregressive moving average (ARMA) graph filter. We devise theoretical performance guarantees on the filter performance when the quantization stepsize is fixed or changes dynamically over the filtering iterations. For FIR filters, we show that a dynamic quantization stepsize leads to more control on the quantization noise than the fixed-stepsize quantization. For ARMA graph filters, we show that decreasing the quantization stepsize over the iterations reduces the quantization noise to zero at the steady-state. In addition, we propose robust filter design strategies that minimize the quantization noise for both time-invariant and time-varying networks. Numerical experiments on synthetic and two real data sets corroborate our findings and show the different trade-offs between quantization bits, filter order, and robustness to topological randomness