Node activity scheduling and routing in Wireless Sensor Networks

Participants : Cédric Adjih, Ichrak Amdouni, Pascale Minet.

The need to maximize network lifetime in wireless ad hoc networks and especially in wireless sensor networks requires the use of energy efficient algorithms and protocols. Motivated by the fact that a node consumes the least energy when its radio is in sleep state, we achieve energy efficiency by scheduling nodes activity. Nodes are assigned time slots during which they can transmit and they can turn off their radio when they are neither transmitting nor receiving. Compared to classical TDMA-based medium access scheme, spatial bandwidth use is optimized: non interfering nodes are able to share the same time slots, collisions are avoided and overhearing and interferences are reduced.

In 2014, we study the issue of delay optimization and energy efficiency in grid wireless sensor networks (WSNs). We focus on STDMA (Spatial Reuse TDMA)) scheduling, where a predefined cycle is repeated, and where each node has fixed transmission opportunities during specific slots (defined by colors). We assume a STDMA algorithm that takes advantage of the regularity of grid topology to also provide a spatially periodic coloring ("tiling" of the same color pattern). In this setting, the key challenges are: 1) minimizing the average routing delay by ordering the slots in the cycle 2) being energy efficient. Our work follows two directions: first, the baseline performance is evaluated when nothing specific is done and the colors are randomly ordered in the STDMA cycle. Then, we propose a solution, ORCHID that deliberately constructs an efficient STDMA schedule. It proceeds in two steps. In the first step, ORCHID starts form a colored grid and builds a hierarchical routing based on these colors. In the second step, ORCHID builds a color ordering, by considering jointly both routing and scheduling so as to ensure that any node will reach a sink in a single STDMA cycle. We study the performance of these solutions by means of simulations and modeling. Results show the excellent performance of ORCHID in terms of delays and energy compared to a shortest path routing that uses the delay as a heuristic. We also present the adaptation of ORCHID to general networks under the SINR interference model.

Time slot and channel assignment in multichannel Wireless Sensor Networks

Participants : Pascale Minet, Ridha Soua, Erwan Livolant.

Applying WSNs in industrial environment requires fast and reliable data gathering (or data convergecast). If packets are forwarded individually to the sink, it is called raw data convergecast. We resort to the multichannel paradigm to enhance the data gathering delay, the robustness against interferences and the throughput. Since some applications require deterministic and bounded convergecast delays, we target conflict free joint time slot and channel assignment solutions that minimize the schedule length. Such solutions allow nodes to save energy by sleeping in any slot where they are not involved in transmissions.

After a comprehensive survey on multichannel assignment protocols in wireless sensor networks, we study raw convergecast in multichannel wireless sensor networks (WSNs) where the sink may be equipped with multiple radio interfaces. We propose $Wave$,a simple, efficient and traffic-aware distributed joint channel and time slot assignment for raw convergecast. Our target is to minimize the data gathering delays and ensure that all packets transmitted in a cycle are delivered to the sink in this cycle, assuming no packet loss at the physical layer. We evaluate the number of slots needed to complete the convergecast by simulation and compare it to the optimal schedule and to a centralized solution. Simulations results indicate that our heuristic is not far from the optimal bound for raw convergecast. Unlike most previously published papers, $Wave$ does not suppose that all interfering links have been removed by channel allocation. In addition, $Wave$ is able to easily adapt to traffic changes. $Wave$ could be used to provide the schedule applied in the $802.15.4e$ TSCH based networks.

Optimized WSN Deployment

Participants : Ines Khoufi, Pascale Minet, Erwan Livolant.

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 a temporary industrial worksite, damage assessment after a disaster.... Many of these applications require the full coverage of the area considered. 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.

In the literature, many studies assume that this area is rectangular and adopt the classical deployment in triangular lattice that has been proved optimal. In real life, things are more complex. For instance, in an industrial worksite, the area to cover has an irregular shape with many edges and is not necessarily convex. Moreover, few papers take obstacles into account. Those that do assume that obstacles are constituted by a juxtaposition of rectangles that seems an unrealistic assumption. In real deployments, the shape of obstacles may be irregular. 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. That is why we focus on the deployment of wireless sensor nodes in an arbitrary realistic area with an irregular shape, and with the presence of obstacles that may be opaque. Moreover, we propose a method that tends to minimize the number of sensor nodes needed to fully cover such an area.

Mobile robots can be used to deploy static wireless sensor nodes to achieve the coverage and connectivity requirements of the applications considered. Many solutions have been provided in the literature to compute the set of locations where the sensor nodes should be placed. We show how this set of locations can be used by a mobile robot to optimize its tour to deploy the sensor nodes to their right locations. In order to reduce both the energy consumed by the robot, its exposure time to a hostile environment, as well as the time at which the wireless network becomes operational, the optimal tour of the robot 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 Robot Deploying Sensor nodes problem, in short RDS. We first show how this problem differs from the well-known traveling salesman problem. We then propose an integer linear program formulation of the RDS 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 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.

Opportunistic routing cross-layer schemes for low duty-cycle wireless sensor networks

Participants : Mohamed Zayani, Paul Muhlethaler.

This is a joint work with Nadjib Aitsaadi from University of Paris 12.

The opportunistic aspect of routing is suitable with such networks where the topology is dynamic and protocols based on topological information become inefficient. Previous work initiated by Paul Muhlethaler and Nadjib Aitsaadi consisted in a geographical receiver-oriented scheme based on RI-MAC protocol (Receiver-Initiated MAC). This scheme is revised and a new contribution proposes to address the same problem with a sender-oriented approach. After scrutinising different protocols belonging to this classification, the B-MAC protocol is chosen to build a new opportunistic cross-layer scheme. Our choice is motivated by the ability of this protocol to provide to a sender the closest neighbor to the destination (typically a sink). In other words, such a scheme enables us to obtain shorter paths in terms of hops which would increase the efficiency of information delivery. In counterparts, as it relies on long preambles (property of B-MAC) to solicit all the neighborhood, it needs larger delays and energy consumption (1% of active time). Nevertheless, this proposal remains interesting as the studied networks are dedicated to infrequent event detection and are not real time-oriented.

When we use BMAC with opportunistic routing, one main advantage is that there is no transmission when there is no event detected in the network in contrast to RI-MAC where beacons of awaking nodes are periodically sent. However, when an event occurs in the area monitored, the end-to-end delay to deliver the alert packet to the sink is much greater with BMAC than with RI-MAC. This may pose problem to some real-time applications. We have propose a scheme where, instead of sending a long preamble to gather all the neighbor nodes, the packet is directly sent. The acknowledgement of the packet allows tthe sender to know whether (or not) the progression towards the destination is sufficient. If it is not the case the packet is sent again. More neighbor node will be awaken and the progression towards the destination will be improved. The selection of the relay terminates when the progression towards the destination is above a given threshold. Actually this relaying scheme encompasses two levels of opportunism. The first level consists in selecting only the awake nodes, the second level consists in selecting the best nodes among the awake nodes. We can show that doing so only slightly increase the number of hops to reach the sink whereas the delay per hop is largely reduced. Thus the end-to-end is very significantly reduced and we still have the property that there is no transmission when there is no event detected in the network.