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Section: New Results

Wireless Sensor Networks

Time slot and channel assignment in multichannel Wireless Sensor Networks

Participants : Pascale Minet, Ridha Soua, Erwan Livolant.

Wireless sensor networks (WSNs) play a major role in industrial environments for data gathering (convergecast). Among the industrial requirements, we can name a few like 1) determinism and bounded convergecast latencies, 2) throughput and 3) robustness against interferences. The classical IEEE 802.15.4 that has been designed for low power lossy networks (LLNs) partially meets these requirements. That is why the IEEE 802.15.4e MAC amendment has been proposed recently. This amendment combines a slotted medium access with a channel hopping (i.e. Time Slotted Channel Hopping TSCH). The MAC layer orchestrates the medium accesses of nodes according to a given schedule. Nevertheless, this amendment does not specify how this schedule is computed. We propose a distributed joint time slot and channel assignment, called Wave for data gathering in LLNs. This schedule targets minimized data convergecast delays by reducing the number of slots assigned to nodes. Moreover, Wave ensures the absence of conflicting transmissions in the schedule provided. In such a schedule, a node is awake only during its slots and the slots of its children in the convergecast routing graph. Thus, energy efficiency is ensured. We describe in details the functioning of Wave, highlighting its features (e.g. support of heterogeneous traffic, support of a sink equipped with multiple interfaces) and properties in terms of worst case delays and buffer size. We discuss its features with regard to a centralized scheduling algorithm like TMCP and a distributed one like DeTAS. Simulation results show the good performance of Wave compared to TMCP. Since in an industrial environment, several routing graphs can coexist, we study how Wave supports this coexistence.

Centralized Scheduling in TSCH-based Wireless Sensor Networks

Participants : Erwan Livolant, Pascale Minet, Thomas Watteyne.

Scheduling in an IEEE802.15.4e TSCH(Time Slotted Channel Hopping 6TiSCH) low-power wireless network can be done in a centralized or distributed way. When using centralized scheduling, a scheduler installs a communication schedule into the network. This can be done in a standards-based way using CoAP. In this study, we compute the number of packets and the latency this takes, on real-world examples. The result is that the cost is very high using today's standards, much higher than when using an ad-hoc solution such as OCARI. We conclude by making recommendations to drastically reduce the number of messages and improve the efficiency of the standardized approach.

Distributed and Optimized Deployment of WSNs

Participants : Ines Khoufi, Pascale Minet.

This is a joint work with Telecom SudParis: Anis Laouiti.

We are witnessing the deployment of many wireless sensor networks in various application domains such as pollution detection in the environment, intruder detection at home, preventive maintenance in industrial process, monitoring of temporary industrial worksites, damage assessment after a disaster.... Wireless sensor networks are deployed to monitor physical phenomena. The accuracy of the information collected depends on the position of sensor nodes. These positions must meet the application requirements in terms of coverage and connectivity, which therefore requires the use of deployment algorithms. We distinguish two cases: firstly when the nodes are autonomous, and secondly when they are static and the deployment is assisted by mobile robots. In both cases, this deployment must not only meet the application's coverage and connectivity requirements, but must also minimize the number of sensors needed while satisfying various constraints (e.g. obstacles, energy, fault-tolerant connectivity). We distinguished two cases: autonomous and mobile wireless sensor nodes on the one hand, and static wireless sensor nodes on the other hand.

We propose a distributed and optimized deployment of mobile and autonomous sensor nodes to ensure full coverage of the 2D-area considered, as well as network connectivity. With the full coverage of the area, any event occurring in this area is detected by at least one sensor node. In addition, the connectivity ensures that this event is reported to the sink in charge of analyzing the data gathered from the sensors and acting according to these data. This distributed algorithm, called OA-DVFA, can run in an unknown area with obstacles dicovered dynamically. We distinguish two types of obstacles: the transparent ones like ponds in outdoor environment, or tables in an indoor site that only prevent the location of sensor nodes inside them; whereas the opaque obstacles like walls or trees prevent the sensing by causing the existence of hidden zones behind them: such zones may remain uncovered. Opaque obstacles are much more complex to handle than transparent ones and require the deployment of additional sensors to eliminate coverage holes. OA-DVFA is based on virtual forces to obtain a fast spreading of sensor nodes and uses a virtual grid to stop node oscillations and save energy by making sleep redundant nodes. It automatically detects when the maximum area coverage is reached.

We also considered 3D volumes and proposed an algorithm, called 3D-DVFA, also based on virtual forces, to ensure full coverage of 3D volumes and ensure network connectivity. This is a joint work with Nadya Boufares from ENSI, Tunisia. Since applications of such 3D deployments may be limited, we focus on 3D surface covering, where the objective is to deploy wireless sensor nodes on a 3D-surface (e.g. a mountain) to ensure full area coverage and network connectivity. To reach this goal we propose 3D-DVFA-SC, a distributed deployment algorithm based on virtual forces strategy to move sensor nodes.

WSN deployment assisted by mobile robots

Participants : Ines Khoufi, Pascale Minet.

This is a joint work with Telecom SudParis: Anis Laouiti.

Autonomous deployment may be expensive when the number of mobile sensor nodes is very high. In this case, an assisted deployment may be necessary: the nodes' positions being pre-computed and given to mobile robots that place a static sensor at each position. In order to reduce both the energy consumed by the robots, their exposure time to a hostile environment, as well as the time at which the wireless network becomes operational, the optimal tour of robots is this minimizing the delay. This delay must take into account not only the time needed by the robot to travel the tour distance but also the time spent in the rotations performed by the robot each time it changes its direction. This problem is called the Multiple Robot Deploying Sensor nodes problem, in short MRDS. We first show how this problem differs from the well-known traveling salesman problem. We adopt two approaches to optimize the deployment duration. The first one is based on game theory to optimize the length of the tours of two robots (TRDS), and the second is based on a multi-objective optimization, for multiple robots (MRDS). The objectives to be met are: optimizing the duration of the longest tour, balancing the durations of the robot tours and minimizing the number of robots used, while bypassing obstacles.

The TRDS problem is modeled as a non-cooperative game with two players representing the mobile robots, these robots compete for the selection of the sensor nodes to deploy. Each robots tends to maximize its utility function.

We then propose an integer linear program formulation of the MRDS problem. We propose various algorithms relevant to iterative improvement by exchanging tour edges, genetic approach and hybridization. The solutions provided by these algorithms are compared and their closeness to the optimal is evaluated in various configurations.

Sinks Deployment and Packet Scheduling for Wireless Sensor Networks

Participants : Nadjib Achir, Paul Muhlethaler.

The objective of this work is to propose an optimal deployment and distributed packet scheduling of multi-sink Wireless Sensors networks (WNSs). We start by computing the optimal deployment of sinks for a given maximum number of hops between nodes and sinks. We also propose an optimal distributed packet scheduling in order to estimate the minimum energy consumption. We consider the energy consumed due to reporting, forwarding and overhearing. In contrast to reporting and forwarding, the energy used in overhearing is difficult to estimate because it is dependent on the packet scheduling. In this case, we determine the lower-bound of overhearing, based on an optimal distributed packet scheduling formulation. We also propose another estimation of the lower-bound in order to simulate non interfering parallel transmissions which is more tractable in large networks. We note that overhearing largely predominates in energy consumption. A large part of the optimizations and computations carried out in this work are obtained using ILP (Integer Linear Programming) formalization.

Security in wireless sensor networks

Participants : Selma Boumerdassi, Paul Muhlethaler.

Sensor networks are often used to collect data from the environment where they are located. These data can then be transmitted regularly to a special node called a sink, which can be fixed or mobile. For critical data (like military or medical data), it is important that sinks and simple sensors can mutually authenticate so as to avoid data to be collected and/or accessed by fake nodes. For some applications, the collection frequency can be very high. As a result, the authentication mechanism used between a node and a sink must be fast and efficient both in terms of calculation time and energy consumption. This is especially important for nodes which computing capabilities and battery lifetime are very low. Moreover, an extra effort has been done to develop alternative solutions to secure, authenticate, and ensure the confidentiality of sensors, and the distribution of keys in the sensor network. Specific researches have also been conducted for large-scale sensors. At present, we work on an exchange protocol between sensors and sinks based on low-cost shifts and xor operations.

Massive MIMO Cooperative Communications for Wireless Sensor Networks

Participants : Nadjib Achir, Paul Muhlethaler.

This work is a collaboration with Mérouane Debbah (Supelec, France).

The objective of this work is to propose a framework for massive MIMO cooperative communications for Wireless Sensor Networks. Our main objective is to analyze the performances of the deployment of a large number of sensors. This deployment should cope with a high demand for real time monitoring and should also take into account energy consumption. We have assumed a communication protocol with two phases: an initial training period followed by a second transmit period. The first period allows the sensors to estimate the channel state and the objective of the second period is to transmit the data sensed. We start analyzing the impact of the time devoted to each period. We study the throughput obtained with respect to the number of sensors when there is one sink. We also compute the optimal number of sinks with respect to the energy spent for different values of sensors. This work is a first step to establish a complete framework to study energy efficient Wireless Sensor Networks where the sensors collaborate to send information to a sink. Currently, we are exploring the multi-hop case.