Fast sink placement for Gossip-based Wireless Sensor Networks

Abstract

Abstract-In this paper we address the problem of sink placement for Gossip-based Wireless Sensor Networks (GWSN). Sink placement plays an important role in planning and deployment of sensor networks. It is an efficient means to improve performance and achieve design objectives. Sink deployment requires an optimization strategy to search a space of possible placement options, and a performance evaluation method to assess the quality of different sink placements. The stochastic nature of the gossip protocol makes this task challenging for GWSN. Simulation is the most common way to accurately evaluate gossiping performance; however, the time required to obtain statistically significant results is considerable and limits the scalability of the sink deployment process. We use a fast and accurate performance evaluation technique, which exploits specifics of the sink placement problem and significantly reduces evaluation time. In order to further improve the speed of the sink placement procedure we propose a greedy simulated annealing search heuristic that converges fast to a near-optimal placement. We have performed an extensive set of experiments to evaluate the performance of the proposed sink placement framework.

Maximizing lifetime of large-scale wireless sensor networks using multi-objective whale optimization algorithm

“…Many of multi-objective swarm algorithms [23,24] have proposed in the literature such as multi-objective bee colony algorithm [21]. Greedy simulated annealing is utilized to optimize the sink node location [25]. Rani and Devarajan in [20] proposed multi-objective PSO with fuzzy logic (FL) to solve Sensor node location problem to choose the best of the non-dominated solutions that are in the Pareto front [26].…”