Artificial potential field approach in WSN deployment: Cost, QoM, connectivity, and lifetime constraints

• Published in: Computer networks (Amsterdam, Netherlands : 1999) Netherlands : 1999), 2011-01, Vol.55 (1), p.84-105
• Main Authors: Aitsaadi, Nadjib, Achir, Nadjib, Boussetta, Khaled, Pujolle, Guy
• Format: Article
• Language: English
• Subjects: Algorithms; Applied sciences; Artificial potential field; Binary optimization; Business and industry local networks; Combinatorial analysis; Complex systems; Complexity; Computer Science; Exact sciences and technology; Heuristic; Irregularities; Miscellaneous; Network topologies; Networking and Internet Architecture; Networks; Networks and services in france and abroad; Optimization; Optimization algorithms; Organization and planning of networks (techniques and equipments); Potential fields; Proposals; Sensors; Services and terminals of telecommunications; Studies; Systems, networks and services of telecommunications; Tabu search metaheuristic; Telecommunications; Telecommunications and information theory; Telemetry. Remote supervision. Telewarning. Remote control; Teleprocessing networks. Isdn; Wireless networks; WSN deployment; ZigBee
• ISSN: 1389-1286; 1872-7069
• DOI: 10.1016/j.comnet.2010.07.017

In this paper, we address a wireless sensor network deployment problem. It is considered when the deployment field is characterized by a geographical irregularity of the monitored event. Each point in the deployment area requires a specific minimum guarantee of event detection probability. Our objective is to generate the best network topology while minimizing cost of deployment, ensuring quality of monitoring and network connectivity, and optimizing network lifetime. The problem is formulated as combinatorial optimization problem, which is NP-complete. Unfortunately, due to the large solution state space and the exponential computational complexity, the exact methods can be applied only in the case of small-scale problem. To overcome the complexity of an optimal resolution, we propose new scalable deployment heuristics based on artificial potential field and Tabu search metaheuristic, namely potential field deployment algorithm ( PFDA) and multi-objective deployment algorithm ( MODA). We compare our proposal to the related deployment strategies, the obtained results show that PFDA and MODA obtain the best performances.