CoReDac: Collision-Free Command-Response Data Collection

Intenerg

Improving sensor network robustness with multi-channel convergecast

Intenerg

A Green TDMA Scheduling Algorithm for Prolonging Lifetime in Wireless Sensor Networks

Fast data collection is one of the most important research issues for Wireless Sensor Networks (WSNs). In this paper, a TMDA based energy consumption balancing algorithm is proposed for the general k-hop WSNs, where one data packet is collected in one cycle. The optimal k that achieves the longest network life is obtained through our theoretical analysis. Required time slots, maximum energy consumption and residual network energy are all thoroughly analyzed in this paper. Theoretical analysis and simulation results demonstrate the effectiveness of the proposed algorithm in terms of energy efficiency and time slot scheduling

MODESA: An optimized multichannel slot assignment for raw data convergecast in wireless sensor networks

International audienceIn aerospace applications, wireless sensor networks (WSNs) collect data from sensor nodes towards a sink in a multi-hop convergecast structure. The throughput requirement of these applications is difficult to meet with a single wireless channel. That is why, in this paper, we focus on a multichannel time slot assignment that minimizes the data gathering cycle. We first formalize the problem as a linear program and compute the optimal time needed for a raw data convergecast in various multichannel topologies. These optimal times apply to sinks equipped with one or several radio interfaces. We then propose our algorithm called MODESA and prove its optimality in various multichannel topologies. We evaluate its performances in terms of number of slots, maximum buffer size and number of active/sleep switches per node. Furthermore, we present variants of MODESA achieving a load balancing between the channels used

Real-Time and Energy-Efficient Routing for Industrial Wireless Sensor-Actuator Networks

With the emergence of industrial standards such as WirelessHART, process industries are adopting Wireless Sensor-Actuator Networks (WSANs) that enable sensors and actuators to communicate through low-power wireless mesh networks. Industrial monitoring and control applications require real-time communication among sensors, controllers and actuators within end-to-end deadlines. Deadline misses may lead to production inefficiency, equipment destruction to irreparable financial and environmental impacts. Moreover, due to the large geographic area and harsh conditions of many industrial plants, it is labor-intensive or dan- gerous to change batteries of field devices. It is therefore important to achieve long network lifetime with battery-powered devices. This dissertation tackles these challenges and make a series of contributions. (1) We present a new end-to-end delay analysis for feedback control loops whose transmissions are scheduled based on the Earliest Deadline First policy. (2) We propose a new real-time routing algorithm that increases the real-time capacity of WSANs by exploiting the insights of the delay analysis. (3) We develop an energy-efficient routing algorithm to improve the network lifetime while maintaining path diversity for reliable communication. (4) Finally, we design a distributed game-theoretic algorithm to allocate sensing applications with near-optimal quality of sensing

Delay Optimized Time Slot Assignment for Data Gathering Applications in Wireless Sensor Networks

International audienceWireless sensor networks, WSNs, are an efficient way to deal with low-rate communications in confined environments such as mines or nuclear power plants because of their simplicity of deployment and low cost. In these application domains, WSNs are used to gather data from sensor nodes towards a sink in a multi-hop convergecast structure. In this paper, we focus on a traffic-aware time slot assignment minimizing the schedule length for tree topologies and for two special deployments (i.e. linear and multi-linear) representative of unusual environments. We formalize the problem as a linear program and provide results on the optimal number of slots. We then propose a delay optimized algorithm with two heuristics that minimize on the one hand the energy consumption and on the other hand the storage capacity as secondary criteria

Optimal Schedules for Data Gathering in Wireless Sensor Networks

Wireless Sensor Networks (WSNs) are widely used for target monitoring: sensors monitor a set of targets, and forward the collected or aggregated data using multi-hop routing to the same location, called the sink. The resulting communication scheme is called ConvergeCast or Aggregated ConvergeCast. Several researchers studied the ConvergeCast and the Aggregated ConvergeCast, as to produce the shortest possible schedule that conveys all the packets or a packet aggregation to the sink. Nearly all proposed methods proceed in two steps, first the routing, and then the scheduling of the packets along the routes defined in the first step. The thesis is organized around four contributions. The first one is an improvement of the previous mathematical models that outputs (minimum-sized) multi-set of transmission configurations (TCs), in which a transmission configuration is defined as a set of links that can transmit concurrently. Our model allows the transmission of several packets per target, in both single-path and multi-path settings; we give two new heuristics for generating new improved transmission configurations. While such models go beyond the routing step, they do not specify an ordering over time of the configurations. Consequently, the second contribution consists of several algorithms, one exact and several heuristics, for ordering the configurations. Our results show that the approach of scheduling when restricted to a tree generated by the first contribution significantly outperforms the ordering of configurations of TC-approach for single-rate, single packet per sensor traffic patterns, but the TC approach gives better results for multi-rate traffic and when there are a large number of packets per sensor. In the last two contributions, we propose an exact mathematical model that takes care, in a single phase, of the routing and the scheduling, for the ConvergeCast and the aggregated ConvergeCast problem. They both correspond to decomposition models in which not only we generate transmission configurations, but an ordering of them. We performed extensive simulations on networks with up to 70 sensors for both ConvergeCast and Aggregated ConvergeCast, and compared our one phase results with one of the best heuristics in the literature

Convergecast with Unbounded Number of Channels

We consider a problem of minimum length scheduling for the conflict-free aggregation convergecast in wireless networks in a case when each element of a network uses its own frequency channel. This problem is equivalent to the well-known NP-hard problem of telephone broadcasting since only the conflicts between the children of the same parent are taken into account. We propose a new integer programming formulation and compare it with the known one by running the CPLEX software package. Based on the results of a numerical experiment, we concluded that our formulation is more preferable in practice to solve the considered problem by CPLEX than the known one. We also propose a novel heuristic algorithm, which is based on a genetic algorithm and a local search metaheuristic. The simulation results demonstrate the high quality of the proposed algorithm compared to the best known approaches