Search

International audience; Collaborative Body Sensor Network (CBSN) is formed of several Body Sensor Networks (BSNs) moving in a given area and able to exchange data between each other. One of the challenges in CBSN is to design a Medium Access Protocol that efficiently supports nodes mobility, and at the same time, that guarantees immediate delivery of urgent data, and maintains high energy efficiency during regular observation. In this paper, a hybrid Traffic and Mobility Aware MAC (TMA-MAC) is proposed to satisfy CBSN's traffic requirements through adopting a hybrid DS-CDMA/DTDMA technique, and to support CBSN's nodes mobility through ensuring efficient transmission of intra-cluster mobile nodes data and proposing a mechanism to handle inter-cluster nodes joining requests. TMA-MAC was compared to other existing protocols under both traffic and mobility variations. Simulations were conducted using OPNET to evaluate TMA-MAC with respect to packet delay, packet drop percentage, and energy consumption.

International audience; Mobile Wireless Sensor Network (MWSN) is a set of interconnected mobile sensor devices forming a dynamic network without a fixed administration. MWSN is used in various domains, such as disaster detection, medical systems, military applications, vehicular communications, and in other sensitive applications. Compared to the classical sensor networks, MWSNs involve an additional constraint consisting of the topology change frequency caused by the mobility of sensor devices. This influences highly the energy consumption and consequently the network reliability. In this paper, we take in charge this important issue and we contribute by the proposition of an efficient and energy-aware routing protocol. The proposed protocol operates for both request and event oriented MWSN applications. It introduces the sensor device mobility history in order to build-up stable routing paths, and incorporates a novel technique of dissimulation in order to exchange the mobility control messages without overhead. We have evaluated the performances of the proposed protocol through simulations, in which it provides effective results in terms of energy consumption and load-balancing.

Imperfection may affect the real world application performance in wireless sensor domain. Therefore, in this article, positions, communication and monitoring radii, as well as energy reserve are, in this article, considered as an uncertain criteria and sensor nodes as information sources. The combination of these uncertain criteria by Dempster-Shafer operation selects the most efficient node for covering each geographical subarea. The problem is how to define the mass function. This paper proposes a fuzzy / evidence model to initialize mass function in the Evidence Theory. Comparing our proposed model, called FDCDAC, with two basic protocols from the literature (the OGCD and TGJD protocols) and with the new protocol FPCOA, shows a better performance and a slight improvement.

Wireless sensor networks are based on a large number of sensor nodes used to measure information like temperature, acceleration, displacement, or pressure. The measurements are used to estimate the state of the monitored system or area. However, the quality of the measurements must be guaranteed to ensure the reliability of the estimated state of the system. Actually, sensors can be used in a hostile environment such as, on a battle field in the presence of fires, floods, earthquakes. In these environments as well as in normal operation, sensors can fail.The failure of sensor nodes can also be caused by other factors like: the failure of a module (such as the sensing module) due to the fabrication process models, loss of battery power and so on. A wireless sensor network must be able to identify faulty nodes. Therefore, we propose a probabilistic approach based on the Hidden Markov Model to identify faulty sensor nodes. Our proposed approach predicts the future state of each node from its actual state, so the fault could be detected before it occurs. We use an aided judgment of neighbour sensor nodes in the network. The algorithm analyses the correlation of the sensors’ data with respect to its neighbourhood. A systematic approach to divide a network on cliques is proposed to fully draw the neighbourhood of each node in the network. After drawing the neighbourhood of each node (cliques), damaged cliques are identified using the Gaussian distribution theorem. Finally, we use the Hidden Markov Model to identify faulty nodes in the identified damaged cliques by calculating the probability of each node to stay in its normal state. Simulation results demonstrate our algorithm is efficient even for a huge wireless sensor network unlike previous approaches.

International audience; Hosting multiple applications in a shared infrastructure of wireless sensor networks is a trend nowadays, and sharing sensory data for answering concurrent applications is a promising and energy-efficient strategy. To address this challenge, this paper proposes an energy-efficient query optimization mechanism for supporting multiple concurrent applications leveraging our two-tier cooperative caching mechanism. Specifically, query requests for concurrent applications are represented as binary strings, which are reduced to a single one for avoiding the reprocessing of shared subquery requests. This reduced query request is answered through our cooperative caching mechanism, where sensory data, which are highly possible to be reused for answering forthcoming query requests, are cached at the sink node (SN). Besides, the gray model GM(1, 1) is adopted for forecasting sensory data units which may be interested mostly by forthcoming query requests. These units of sensory data may be prefetched from the network and cached at the SN. Experimental evaluation shows that this approach can reduce the energy consumption significantly, and improve the network capacity to an extent, especially when the number of concurrent query requests is relatively large

International audience; Battery lifetime is a key impediment to long-lasting low power sensor nodes and networks thereof. Energy harvesting—conversion of ambient energy into electrical energy—has emerged as a viable alternative to battery power. Indeed, the harvested energy mitigates the dependency on battery power and can be used to transmit data. However, unfair data delivery delay and energy expenditure among sensors remain important issues for such networks. We study performance of sensor networks with mobile sinks: a mobile sink moves towards the transmission range of the different static sensor nodes to collect their data. We propose and analyse a Markovian queueing system to study the impact of uncertainty in energy harvesting, energy expenditure, data acquisition and data transmission. In particular, the energy harvesting sensor node is described by a system with two queues, one queue corresponding to the battery and the other to the data buffer. We illustrate our approach by numerical examples which show that energy harvesting correlation considerably affects performance measures like the mean data delay and the effective data collection rate.

International audience; The energy efficiency of Wireless Sensor Networks (WSNs) is considerably improved with Wake-up Radio (WuR) systems. However, their resilience to interference is often neglected in the literature. This might be an issue due to the proliferation of wireless devices and the growing field of internet of things. In this paper, we evaluate the impact of in-band interference from wireless devices on a WuR system. The approach proves that WuR systems are still performing well when coexisting with external wireless networks, even if the energy-efficiency is slightly reduced.

International audience; In wireless sensor networks, a serial processing algorithm browses nodes one by one and can perform different tasks such as: creating a schedule among nodes, querying or gathering data from nodes, supplying nodes with data, etc. Apart from the fact thatserial algorithms totally avoid collisions, numerous recent works have confirmed that these algorithms reduce communications andconsiderably save energy and time in large-dense networks. Yet, due to the path construction complexity, the proposed algorithmsare not optimal and their performances can be further enhanced. To do so, in the present paper, we propose a new serial processing algorithm that, in most of the cases, approximates the optimal number of hops (i.e., it requires n − 1 communications to traverse a network of n nodes). The extensive OMNeT++ simulations confirm the outperformance and efficiency of the proposal in terms of scalability and energy/time consumption.

International audience; In this paper, the optimal sensor location problem is first discussed for environmental monitoring of physical phenomena governed by some advection-diffusion partial-differential equations. In particular, the exact derivation of the observability Gramian of an advection-diffusion PDE is investigated. Based on the optimality criteria derived from this analysis, a conservation law governing the behavior of a crowd of mobile sensors is proposed to ensure convergence of the sensor density towards an optimal location. The monitoring of pollution on a 2D domain is the case study used throughout the paper to illustrate the effectiveness of the proposed approach.

International audience; A large use of applications of Wireless Sensor Networks (WSNs) pushes researchers to design and improve protocols and algorithms against the encountered challenges. One of the main goals is data gathering and routing to the base station (through the sink nodes) with lack of acknowledgement and where each node has no information about the network. Unbalanced energy consumption during the data routing process is an inherent problem in WSNs due to the limited energy capacity of the sensor nodes. In fact, WSNs require load balancing algorithms that make judicious use of the limited energy resource to route the gathered data to the sink node. In this paper, we propose a balanced multi-path routing algorithm by focusing on the residual energy and the hop count of each node to discover the best routes and to insert them into the routing table. The main idea of this algorithm comes from Ant Colony Optimization (ACO) and automata network modelization. Hence, the potential performance of the proposed algorithm relies on the best route to be selected which should have the minimum number of hops, the maximum energy and weighted energy between participating nodes to extend the lifetime of the network.

International audience; To meet severe aeronautic environment constraints, we propose in this paper a versatile 794μW autonomous multi-power-source wireless sensor system interfacing with aeronautic-grade resistive bridge transducers and operating over a wide range of -40°C to +180°C in 180nm HT SOI technology. Compared to previously reported works, it provides robust and versatile 8Sps-1kSps sensor interface and RFID/micro wind turbine power supply scheme.

Wireless sensor networks have been widely deployed in the last decades to provide various services, like environmental monitoring or object tracking. Such a network is composed of a set of sensor nodes which are used to sense and transmit collected information to a base station. To achieve this goal, two properties have to be guaranteed: (i) the sensor nodes must be placed such that all the environment of interest is covered, and (ii) every sensor node can transmit its data to the base station (through other sensor nodes). In this paper, we consider the Minimum Connected Coverage (MCC) problem. We propose two mathematical programming formulations for the MCC problem on square grid graphs. We compare them to a recent model proposed by Rebai et al [1]. Our mathematical programming formulations yield a better LP-bound at the root of the branch-and-cut process than the model of Rebai et al. Moreover, the presented formulations outperform the proportion of solved instances in their work as well as the CPU computation time and the number of nodes explored in the tree search.

International audience; The Content-Centric Networking (CCN) concept is a significant approach of several future Internet research activities. CCN in Wireless Sensor Networks present a promised technique that may ensure data routing based on content. In this paper, we focus on the lifetime of the Content Object exchanged in the network and we explain the idea of its integration in CCN for WSNs to better highlight the relevance of its exploitation. To this end, we implement DFCCN-WSNs 'Data Freshness aware Content-Centric Networking in Wireless Sensor Networks' a protocol that implements the data lifetime. Through extensive simulations, we demonstrate that DFCCN-WSNs outperforms traditional CCN in terms of end-to-end delay.

International audience; In wireless sensor networks with linear topology, knowing the physical order in which nodes are deployed is useful not only for the target application, but also to some network services, like routing or data aggregation. Considering the limited resources of sensor nodes, the design of autonomous protocols to find this order is a challenging topic. In this paper, we propose a distributed and iterative centroid-based algorithm to address this problem. At each iteration, the algorithm selects two virtual anchors and finds the order of a subset of nodes, placed between these two anchors. The proposed algorithm requires local node connectivity knowledge and the identifier of the first sensor node of the network, which is the only manually configured parameter. This solution, scalable and lightweight from the deployment and maintenance point of view, is shown to be robust to connectivity degradation, correctly ordering more than 95% of the nodes, even under very low connectivity conditions

International audience; Wireless Sensor Networks (WSNs) are arising from the pro- liferation of Micro-Electro-Mechanical Systems (MEMS) tech- nology as an important new area in wireless technology. They are composed of tiny devices which monitor physi- cal or environmental conditions such as temperature, pres- sure, motion or pollutants, etc. Moreover, the accuracy of individual sensor node readings is decisive in WSN ap- plications. Hence, detecting nodes with faulty sensors can strictly influence the network performance and extend the network lifetime. In this paper, we propose a new approach for faulty sensor node detection in WSNs based on Copula theory. The obtained experimental results on real datasets collected from real sensor networks show the effectiveness of our approach.

International audience; In Wireless Sensor Networks (WSNs), routing data towards the sink leads to unbalanced energy consumption among intermediate nodes resulting in high data loss rate. The use of multiple Mobile Data Collectors (MDCs) has been proposed in the literature to mitigate such problems. MDCs help to achieve uniform energy-consumption across the network, fill coverage gaps, and reduce end-to-end communication delays, amongst others. However, mechanisms to support MDCs such as location advertisement and route maintenance introduce significant overhead in terms of energy consumption and packet delays. In this paper, we propose a self-organizing and adaptive Dynamic Clustering (DCMDC) solution to maintain MDC-relay networks. This solution is based on dividing the network into well-delimited clusters called Service Zones (SZs). Localizing mobility management traffic to a SZ reduces signaling overhead, route setup delay and bandwidth utilization. Network clustering also helps to achieve scalability and load balancing. Smaller network clusters make buffer overflows and energy depletion less of a problem. These performance gains are expected to support achieving higher information completeness and availability as well as maximizing the network lifetime. Moreover, maintaining continuous connectivity between the MDC and sensor nodes increases information availability and validity. Performance experiments show that DCMDC outperforms its rival in the literature. Besides the improved quality of information, the proposed approach improves the packet delivery ratio by up to 10%, end-to-end delay by up to 15%, energy consumption by up to 53%, energy balancing by up to 51%, and prolongs the network lifetime by up to 53%.

International audience; Wireless sensor networks (WSNs) are almost everywhere, they are exploited for thousands of applications in a densely distributed manner. Such deployment makes WSNs one of the highly anticipated key contributors of the big data nowadays. Hence, data aggregation is attracting much attention from researchers as efficient way to reduce the huge volume of data generated in WSNs by eliminating the redundancy among sensing data. In this paper, we propose an efficient data aggregation technique for clustering-based periodic wireless sensor networks. Further to a local aggregation at sensor node level, our technique allows cluster-head (CH) to eliminate redundant data sets generated by neighboring nodes by applying three data aggregation methods. These proposed methods are based on the sets similarity functions, the one-way Anova model with statistical tests and the distance functions respectively. Based on real sensor data, we have analyzed their performances according to the energy consumption and the data latency and accuracy, and we show how these methods can significantly improve the performance of sensor networks.

International audience; In wireless sensor networks, building energy-efficient systems is one of the major challenges. In such networks, nodes are usually supplied by low power and small batteries. Many factors are involved in the energy consumption, and this issue may be considered as a cross-layer problem, from the hardware architecture to the application layer. This paper aims at presenting a hybrid solution for sensor networks based on two main aspects. The first one is the hardware architecture, where we present a prototype of a sensor node we designed. This node proved its efficiency in terms of energy consumption. The second aspect is related to the topology construction and presents a new topology control algorithm based on graph computing. Thus, our system consists of a real indoor application for temperature and humidity monitoring, applicable to home automation or industrial monitoring. We performed the experiments using a set of sensor nodes deployed over a building and proved the efficiency of the system in terms of energy consumption, network lifetime and data delivery.

Geographic protocols have been recently developed for data routing in wireless ad hoc networks. These protocols are based on the exact location of each sensor node, by assuming that sensor nodes are equipped with geographic positioning services or localization-based techniques. At each node, the routing decision is based only on the position of the destination node and the position of the forwarding node’s neighbors. Location-based techniques, such DV-Hop, have attracted a lot of interest in order to estimate nodes positions. In this paper, we evaluate the performance of DV-Hop localization technique for estimating nodes localization and integrate it within the greedy perimeter stateless routing protocol. Simulations have been conducted to show the effectiveness of using localization-based techniques when integrated into geographical routing protocols for wireless sensor networks.

International audience

Wireless Sensor Networks (WSN) consist of sensor nodes with sensing and communication capabilities. Since sensor nodes are energy constrained and sensor data are subject to several sources of errors, the use of a quorum mechanism to achieve consensus leads to higher data accuracy. In this paper, an Event Clustering Routing Protocol based on Consensus (ECRPC) is proposed for WSN. The main idea of ECRPC is based on: (i) No message will be transmitted to the Base Station (BS) provided that a consensus is reached (ii) A tradeoff is made between the two criteria of residual energy and link cost: in certain cases, we give priority to length relay over the energy or vice versa. Simulation results show that ECRPC protocol significantly prolongs the network survival time.

Wireless sensor networks (WSNs) are widely used nowadays in various domains. In general, the applications in which the WSN is deployed need that this network presents a minimal degree of reliability, effectiveness and robustness. However, the specificity of the nodes deployed in this type of networks makes them prone to failures. In this paper, we discuss the recovery from simultaneous failures for a large scale WSN in a multichannel context. Indeed, we propose a deployment scenario which uses thousands of sensor nodes and relay nodes. Then, we propose Simultaneous Failure Recovery based on Relay Node Relocation (SFR-RNR) approach which aims to recover from simultaneous failures. These failures lead to the damage of a whole segment of the WSN, and hence, the loss of the monitored field coverage and/or connectivity. SFR-RNR rearranges a minimal set of relay nodes to restore, partially, the coverage and improve or restore the connectivity; then it reallocates the channels to minimize the interferences. The performance of the proposed approach is evaluated by simulation.

Any radio signal gets exposed to some attenuation over distance, and is received at the receiver as its distorted version and is superposed with other wireless signals transmitted in the neighborhood. In wireless communications, the useful signal is usually decoded by assuming the sum of all other wireless signal transmissions as noise. Interference between coexisting transmissions can cause severe performance degradation in wireless sensor networks (WSNs). In this paper we have reviewed interference models for wireless sensor networks. Since a decade or more, densification of networks increases the impact of interference. New models have been proposed but are not yet included into network simulators. This could be source of a big difference between simulations and real deployments.

International audience; The recent advancements of technology in robotics and wireless communication have enabled the low-cost and large-scale deployment of mobile sensor nodes for target tracking, which is a critical application scenario of wireless sensor networks. Due to the constraints of limited sensing range, it is of great importance to design node coordination mechanism for reliable tracking so that at least the target can always be detected with a high probability, while the total network energy cost can be reduced for longer network lifetime. In this paper, we deal with this problem considering both the unreliable wireless channel and the network energy constraint. We transfer the original problem into a dynamic coverage problem and decompose it into two subproblems. By exploiting the online estimate of target location, we first decide the locations where the mobile nodes should move into so that the reliable tracking can be guaranteed. Then, we assign different nodes to each location in order that the total energy cost in terms of moving distance can be minimized. Extensive simulations under various system settings are employed to evaluate the effectiveness of our solution.

In Wireless Sensor Networks, mobile sensing refers to the presence of one or more mobile sinks or mobile sensors, which have the main role of collecting the gathered data by sensor nodes. This paper describes a new scheme of mobile sensing that aims at providing a good coverage and throughput while maintaining better energy efficiency and high network availability. To achieve this, some features of the social foraging behavior of the Escherichia coli bacteria have been used, especially the chemotaxis and swarming processes that allow bacteria to move. Particularly, a description and a formulation of a mobile sensing scheme based on an approach inspired by the Bacterial Foraging Optimization have been provided. Models that allow mobile sinks to move over the network in a self-organized and self-adaptive way have been proposed. The proposal has been experimented in order to elaborate the impact of mobility on delay, network coverage and successful amount of collected data. The obtained results demonstrate the effectiveness of the proposal.

International audience; To save energy in Wireless Sensor Networks (WSNs) and prolong the network lifetime, many works investigate the use of one or more mobile sinks. These solutions are mainly based on organizing the network within a grid to simplify the computation of the sink trajectory. However, existing solutions do not take into account energy consumption during grid construction and do not scale when the sink has to visit every cell of the network grid.To overcome this drawback, we propose an energy-based cellhead selection combined with two sink mobility algorithms tominimize energy consumption of sensor nodes and optimize data collection. Experimentation results confirm the efficiency of our algorithms compared to two basics schemes, i.e. static sink and random sink mobility and also to the related work.

International audience; High energy consumption of sensor devices is a major problem in smart building systems, since it strongly impacts the system lifetime. However, existing approaches are often fitted to a single monitoring application and rely on static configurations for sensor devices: optimization of their acquisition and transmission frequencies to actual multiple application requirements is not tackled. In this paper, we focus on energy-aware dynamic sensor device re-configuration to lower energy consumption while fulfilling real-time application requirements. We introduce the Smart-Service Stream-oriented Sensor Management (3SoSM) that binds together sensor configuration and management of sensor data streams. We present a multi-application monitoring system architecture that optimizes application requirements for data streams into sensor device configurations, and we relate the experiments with our experimental platform.

International audience; Wireless Sensor Networks (WSNs) are the enabling technology for smart cities, intelligent cars and transportation systems, precision agriculture, animal tracking, and all data collection and sensing-based applications. In most \{WSN\} applications, new sensor nodes are added to the network by post-deployment to assure network connectivity, to replace dead sensor nodes or to cover more regions in the area of interest. This type of network is called Multi-Phase \{WSNs\} (MPWSNs). Similarly to classical WSNs, multi-phase \{WSNs\} require security mechanisms to ensure their deployment. However, these networks need specific solutions adapted to the multiple deployments of nodes. In this paper, we review, classify and compare the existing key management schemes proposed for this type of sensor network. We illustrate both advantages and disadvantages of each multi-phase key management scheme. Finally, we give some directions to design lightweight robust key management for MPWSNs.

International audience; TDMA (Time Division Multiple Access)) is known to be an affective method for energy saving in wireless sensor networks (WSNs). However, when any slot is exclusively reserved to one node, the TDMA-based protocols suffer from low-channel utilization and high data delivery delays. STDMA (Spatial reuse TDMA) avoids these drawbacks by allowing multiple nodes to access the same time slot provided that these nodes do not interfere. The objective of this paper is to evaluate the delay performance of STDMA assuming grid networks and a random ordering of the slots in the STDMA cycle. The evaluation is performed both with a stochastic analytical model and by experiments based on a known STDMA method called VCM. Results show that the random ordering performance is rather good. A framework for STDMA applied to general graphs under SINR interference model is also presented.

International audience; In dense wireless sensor networks, a multichannel MAC is a good means to reduce channel contention and increase frame reception probability. In this paper, we report on experiments with transmissions on various channels in the 2.4GHz ISM band and find more channel diversity than expected: this effect is particularly exacerbated at a short range, but it also has a significant impact at any distance. Moreover, we find that wireless sensor nodes have a radiation pattern that changes significantly with the frequency channel. This feature is inherent to the size of the sensor node, in which the antenna necessarily interferes with other components. The first consequence of this finding is that frequency diversity in sensor networks is even more effective than generally thought, and conversely, single channel communication schemes should be avoided as long as the power budget is not very comfortable. Keywords—802.15.4, coherence band, channel hopping, radio propagation I. INTRODUCTION In the context of a growing number of connected devices forming potentially dense wireless networks, using the whole available spectrum becomes unavoidable. IEEE 802.15.4 defines 16 channels in the 2.4GHz band with the width of 2 MHz and 5 MHz interchannel spacing. Besides segregating the transmissions, changing the channel allows to benefit from the diversity due to the sensitivity of multipath fading to the central frequency. In other words, there can be a channel between two nodes that works well, but during the same time frame, this channel gives very bad performance with other nodes. For all these reasons, the IEEE 802.15.4e-2012 amendment [1] specified channel hopping protocols such as TSCH (Time Synchronized Channel Hopping) or DSME (Deterministic and Synchronous Multi-channel Extension). Even though a lot of research aims at harnessing channel diversity, most of the studies invoke multipath fading as the reason of bad communication on certain channels between two given nodes. Two solutions exist to improve performance: either change the position of a node or the antenna, or change the frequency. The first solution is inapplicable in most cases because access to the node might not always be possible. Taking advantage of antenna diversity is also challenging to implement for cost and space constraints. Fortunately, even for short range and line of sight communications , our experiments show that there is a lot of diversity when changing channels, more than multipath fading itself can explain. We posit that the entire wireless sensor board has a role in radio propagation. On certain frequencies and in many directions, its presence either attenuates the radio signal or amplifies it. This effect is unavoidable for compact nodes and it has a noticeable impact within the band of interest. We start the paper with a simple radio propagation model and present selected real world measurements of commu

International audience; The proliferation of radio communication systems and the significant advances in enabling device technologies are pa- ving towards Internet-of-Things (IoT) and opening new hori- zons for Smart City applications and its services. Such evo- lution becomes essential in order to enhance quality of ur- ban services, to reduce costs, and to engage citizens more actively. In this context, novel simulation tools are required to prepare the future deployments of large-scale IoT infras- tructure for Smart cities in the best conditions in terms of reliability, energy consumption, and cost. This keynote ses- sion presents the CupCarbon framework: a platform for de- signing smart-city and IoT Wireless Sensor Networks (SCI- WSN). CupCarbon aims to provide following benefits that makes it significant from the other conventional wireless sen- sor network simulators.(1) provides modeling and simulation of radio propagation channel and alpha-stable noise based interferences in more realistic way,(2) takes into account the deployment environment and quantify the uncertainty of simulations,(3) allows the representation of mobile nodes and dynamic environments,(4) allows the behavioural study of a network or networks with large number of nodes in practical environments (city, mountain, etc.).The CupCarbon simulator allows it’s user to design, visu- alize, debug and validate distributed algorithms for moni- toring environmental data collections of wireless sensor net- work. It creates environmental scenarios such as fires, gas, mobiles, and generally within educational and scientific pro- jects. It offers two different simulation environments. First is a multi-agent environment that enables the design of mo- bility scenarios and the generation of events such as fires and gas as well as the simulation of mobile nodes. Second en- vironment represents a discrete event simulation of wireless sensor networks which also takes into account the scenario designed on the basis of the first environment.Interference models based on the impulsive nature of noise and outdoor propagation models are embedded within Cup- Carbon to provide more realistic analysis of WSNs for smart city applications. These models are associated with spatial zones according to the electromagnetic interactions.

In this brief, a wireless sensor network in which the nodes are equipped with a programmable middleware that allows the quick deployment of different applications is considered. We propose a distributed method to extend the network lifetime by managing how tasks are assigned to different nodes. A detailed model of energy consumption of the wireless sensor nodes is provided and a gossip-based algorithm that only exploits iterative and asynchronous optimizations involving local information between neighboring nodes to maximize the global network lifetime is proposed. Experimental results and simulations performed on the embedded hardware show that our framework can provide a significant lifetime extension, particularly for networks with high node densities and nonuniform energy consumption or initial battery charge.

In wireless visual sensor networks comprised of multiple camera-enabled sensors, source prioritization can be exploited to soften the impact of congestion, packet loss and energy depletion when higher relevant packets are processed. However, for such optimizations, source nodes have to be properly prioritized according to some effective metric. When performing visual sensing over moving targets, sensors may view different parts of the targets, which may have particular relevance for monitoring applications. In this context, this paper proposes a low-cost mathematical approach that associates a priority level to each visual source node according to the viewed segments of the targets' perimeter, and such priority may then be exploited for a large set of optimizations. A complete mathematical formulation and numerical results are presented to base the proposed approach.

International audience; Localization is an essential issue in wireless sensor networks to process the information retrieved by sensor nodes. This paper presents an indoor zoning-based localization technique that works efficiently in real environments. The targeted area is composed of several zones, the objective being to find the zone where the mobile node is instantly located. The proposed approach collects first strengths of received WiFi signals from neighboring access points and builds a fingerprints database. It then uses belief functions theory to combine all measured data and define an evidence framework, to be used afterwards for estimating the most probable node's zone. Real experiments demonstrate the effectiveness of this approach and its competence compared to state-of-the-art methods.

International audience; In wireless sensor networks, coverage and connectivity are two essential issues. They indicate how all the points of an area of interest are covered and how the sensor devices of the wireless sensor network are connected in an efficient way. In this study, the problem of minimising total grid coverage cost with connectivity constraint is considered. The connectivity constraint means that each deployed sensor has to find a path, composed of connected sensors, until to reach the base station the sink. The problem may be reduced to a 2-dimensional critical grid coverage problem which is an NP-Complete problem. We propose mixed integer linear programming models to solve the problem optimally. We verify by computational experiments that the developed approaches can provide the optimal solution of grid sizes of 15 × 15 width × length in a reasonable time. We also show that one of the proposed methods is more efficient than some methods developed for similar problems.

International audience; Disaster monitoring becomes a requirement for collecting and analysing data in order to offer a better disaster management situation. Periodic sensor networks (PSNs) are usually used in disaster monitoring and are characterised by the acquisition of sensor data from remote sensor nodes before being forwarded to the sink in a periodic basis. The major challenges in PSN are energy saving and collected data reduction in order to increase the sensor network lifetime and to ensure a long-time monitoring for disasters. In this paper, we propose an adaptive sampling approach for energy-efficient periodic data collection in sensor networks. Our proposed approach provides each sensor node the ability to identify redundancy between collected data over time, by using similarity functions, and allowing for sampling adaptive rate. Experiments on real sensors data show that our approach can be effectively used to conserve energy in the sensor network and to increase its lifetime, while still keeping a high quality of the collected data.

The need for energy-efficient routing and data gathering protocols in large-scale environments becomes very challenging. Hierarchical routing in WSNs is a very important topic. It has been widely investigated relative to energy efficiency based routing protocols. LEACH (Low Energy Adaptive Clustering Hierarchy algorithm) is the pioneering cluster routing protocol in WSNs. However, it is not suitable for large scale network and wireless channel conditions are ignored during packet forwarding. To address this issue, we proposed a novel multi-hop clustering cross layer protocol based on LEACH. It considers both the SNR of different links and the residual energy of sensor nodes. Simulation results in terms of the average energy consumption, the network lifetime and the Packet Delivery Ratio show clearly the outperformance of the proposed algorithm versus the conventional LEACH.

International audience; The sensor deployment problem consists in finding an optimal (or near-optimal) way of placing sensors in a given area in order to cover the whole space. However, sometimes it is not necessary to monitor the complete area; one may want to focus on some points considered as target. This leads to the target coverage problem. This problem includes two main processes: (1) placing sensors around the targets, (2) scheduling the activation time redundant sensors in order to lengthen the network lifetime. This paper proposes a multi-objective approach based on genetic algorithms that aims to simultaneously find good positions of sensor nodes and the maximum number of disjoint cover sets. A new chromosome (solution) encoding in which the genes contain both, the position and the identifier of sensor owning group is introduced. The efficiency of the proposed approach is assessed by a comparison with existing methods.

International audience; Wireless sensor networks (WSN) are specially distributed sensors deployed for the purpose of sensing and monitoring physical or environmental conditions. Sensor measurements in WSN usually suffer from both random errors (noise) and systematic errors (bias). This poses a major problem in the end application, as the data from the network become progressively uninformative

International audience; The paper proposes a new approach to model an insect surveillance network as synchronous network systems, systems consist of components running simultaneously. In the network, insects and surrounding environments compose a physical system of which executions proceed concurrently in synchronous rounds. This system is synchronized with a synchronous wireless sensor network, the observation network. The simulation of the case study Brown Planthoppers surveillance network in the Mekong Delta provides some useful information in managing pest insects as well as emerges the roles of wireless sensor network in monitoring environments.

International audience; Wireless Sensor Networks (WSNs) have emerged recently as one of the most attractive research subjects. The resource-constraint characteristics of WSNs limit the secure design and development of security protocols and presumably thwart the integration of an intrusion detection system (IDS). Whilst, sensor nodes which usually operate in unattended and even harsh environments, are prone to failures and vulnerable to malicious attacks. For reliable and secure communications in WSNs, intrusion-tolerant routing becomes possibly a critical attribute that should be integrated into WSNs. However, there was not much research investigated on this topic. In order to provide a useful starting point for researchers interested in the subject, in this paper, we comparatively study two intrusion-tolerant routing protocols for WSNs, namely INSENS and ITSRP. Simulations were especially invested to assess their practicality. We also propose some suggestions to improve these two protocols. Although the feasibility of our suggestions is still questionable and deserves more investigation, we consider this study as the first step to fulfill the design of intrusion-tolerant WSNs as well as to build a complete intrusion-tolerant framework hereafter

Recent advances in the field of intelligent transportation systems have focused on the use of wireless networks to link vehicles and road infrastructure. Applications that might result from such networks range from the adaptive management of traffic lights to the detection of traffic jams and accidents. Whatever the case may be, it seems important to explore the possibilities and limitations of such networks, which the literature often portrays in a somewhat idealistic way (e.g. no packet loss, fully connected sensors, etc.). In this paper, we study the deployment of wireless sensor networks at intersections in some of the world's major cities and characterize their topologies. Using a propagation model that corresponds to a 2.4GHz IEEE 802.15.4 network interface, we focus our study on the global connectivity of graphs resulting from different networks. By deploying this type of network over 52 city and region maps extracted from OpenStreetMap, we show that cities can reasonably be classified into three network structure categories of low connectivity (i.e. a high number of connected components) and that it should be feasible to improve the networks by adding sensors. All the tools and the complete dataset are freely available online.

International audience; Connecting wireless sensor networks (WSN) by the air be- comes attractive due to advances in Satellites and Unmanned aerial vehi- cle (UAV). This work focus on specification and simulation of situations where several distant WSN have gateways visited periodically by a mo- bile on a static path. To develop and evaluate collection and control services, it is first needed to run system level simulation. This paper re- ports on producing automatically representations of complex topology where mobile cooperate with sensor fields with respect to timing con- straints from both sides. Simulation programs are produced for graphic accelerators (GPU), and concurrent process architectures.

International audience; Minimizing the energy consumption and hence ex-tends the network lifetime is a key requirement when designing anefficient sensor network protocol. QoS-aware routing in WirelessSensor Network (WSN), aims to take into account other networksperformance aspects as minimizing end-to-end delay (as well asjitter), reducing packet loss rate while minimizing the energyconsumption of the network during data transmission. Theseobjectives are sometimes conflicting, and therefore tradeoffs mustbe made between energy conservation and QoS considerations.The general problem can be reformulated as a Multi-ConstrainedOptimal Path problem (MCOP), and is known as NP-complete.The latter raises a real challenge, as sensor nodes are verylimited in resources capabilities, we propose to use fuzzy inferencemechanism to seek a good tradeoff between all given metricsand constraints. This paper discusses the implementation ofcombining several routing metric, using fuzzy logic to design aRPL objective function, the routing standard for the Internet ofThings. The proposal is integrated on Contiki operating systemand his deployment were performed on a real world indoor WSN.Obtained results show improvements compared to the commonimplementation of the RPL protocol, and demonstrate relevanceof our contribution.

International audience; Wireless sensor network (WSN) consists of a large number of low-power, limited-processing capability, MEMS (Micro-Electromechanically Systems) capable of measuring and reporting physical variables related to their environment. WSN (p,n) is a wireless sensor network of p sensors with n items (information) distributed on it. The aim of the permutation routing is to route to each sensor, its n/p items (packets), so it can accomplish its task. In this paper, we are interested in the permutation routing problem on WSN (p,n) when the network is multi-hop. We propose new protocols that perform efficiently with respect to the number of broadcast rounds and run without conflict and collision on the communication channels. The main idea to have a collision-free protocol is to use distributed algorithms to give colors for sensor nodes. Using these colors nodes route the information in parallel until each node receives all its items. Simulation results are presented to give a comparison and show the performances and the effectiveness of our protocols.

International audience; A main reason to the growth of wireless sensor networks deployed worldwide is their easy and fast deployment. In this paper we consider deployments assisted by mobile robots where static sensor nodes are deployed by mobile robots in a given area. Each robot must make a tour to place its sensor nodes. All sensor nodes must be placed at their precomputed positions. The Multi-Robot Deploying wireless Sensor nodes problem, called the MRDS problem, consists in minimizing the longest tour duration (i.e. the total deployment duration), the number of robots used and the standard deviation between duration of robots tours. After a formal definition of the MRDS problem, we show how to use a multi-objective version of genetic algorithms, more precisely the NSGA-II algorithm, to solve this multi-objective optimization problem. The solutions belonging to the best Pareto front are given to the designer in charge of selecting the best trade-off taking into account various criteria. We then show how to extend this method to take obstacles into account, which is more representative of real situations.

International audience; Wireless sensor networks are a challenging field of research when it comes to security issues. Using low cost sensor nodes with limited resources makes it difficult for cryptographic algorithms to function without impacting energy consumption and latency. In this paper, we focus on key management issues in multi-hop wireless sensor networks. These networks are easy to attack due to the open nature of the wireless medium. Intruders could try to penetrate the network, capture nodes or take control over particular nodes. In this context, it is important to revoke and renew keys that might be learned by malicious nodes. We propose several secure protocols for key revocation and key renewal based on symmetric encryption and elliptic curve cryptography. All protocols are secure, but have different security levels. Each proposed protocol is formally proven and analyzed using Scyther, an automatic verification tool for cryptographic protocols. For efficiency comparison sake, we implemented all protocols on real testbeds using TelosB motes and discussed their performances.

International audience; The use of wireless sensor networks (WSNs) isgrowing up in the last few years. Therefore, new challengesarise every day and one of the emerging challenges in WSNsis the nodes mobility support. This feature increases theapplication areas of these technologies but also raises newchallenges to solve. This paper proposes a new handovermechanism, called Hand4MAC (Handover mechanism forMAC layer supporting continuous communication in mobilewireless sensor networks), to deal with body sensorsmobilityin scenarios where patients are hospitalized. This approachtries to provide continuous monitoring and communicationwith these sensor nodes when they move across differentaccess points wireless coverage range. The proposed methodfor medium access control (MAC) layer considers that nodesremain within the same network. The evaluation study of theproposed algorithm was performed by simulation and evaluatedin comparison with the well-known RSSI-based handoveralgorithm. Itwas concluded that Hand4MAC performsbetter and reveals promising results for real deployment.

International audience; Recent applications of Wireless Sensor Network require small yet sustainable battery-powered devices. As a consequence, it becomes crucial to accurately and efficiently compute a node???s power consumption in order to estimate its lifetime. Existing wireless network simulators either implement simplistic energy consumption and battery models, or very complex and general ones that hinders scalability. In this paper, we (i) present WiSeBat, a module to estimate devices lifetime using realistic energy consumption and battery models, that has specially been optimized for wireless sensor network simulations. We then (ii) validate it through real measurements. Finally, we used it (iii) to compare wireless sensor lifetime in several realistic scenarios. Firstly, we review existing techniques to simulate a battery and discuss what behaviors are important to get realistic and fast simulations. We then propose simulator-independent models for the battery and for the energy consumption of sensors, and implement this model in the WSNet simulator. Secondly, we compare measured and simulated lifetimes of sensors. On the one hand, our experiments show that our models provide an 86 -- 96% accurate lifetime estimation. On the other hand, the previous default WSNet models overestimate lifetime by more than 2600%. Once validated, we used our approach to benchmark the energy consumption of different protocol stacks of wireless sensor networks, under different scenarios. These simulations match well-known results in simple scenarios, as we demonstrate better performance of ContikiMAC over X-MAC. They also provide an accurate comparison of sensor lifetime in more complex scenarios.

International audience; In this paper, we apply the Gilbert-Elliot model to analyze measurements on a large-scale wireless sensor testbed with nodes equipped with CC1101 and CC2420 radio chips. The model considers a packet loss process as a sequence of transitions between Good and Bad states. We analyze the Packet Reception Ratio (PRR) based on the probabilities derived from the Gilbert-Elliot model. We show that the probabilities and other parameters (run and loss lengths) can very well discriminate between the main categories of link quality such as good and weak links. Identification of link quality is crucial for routing protocols such as RPL and LOADng.