Optimization Techniques in Wireless Sensor Networks

Meta-heuristic algorithms have been widely used for developing new algorithms and optimizing different aspects in wireless sensor networks (WSNs). In most complicated problems, it is needed to evaluate a multitude of possible modes, to obtain an exact solution. Meta-heuristic algorithms can produce solution in acceptable time constraints. These algorithms play an effective role in solving such problems by optimizing the different metrics such as coverage rate and energy consumption of the networks. These metrics have valuable impact on network lifetime as well. In this paper, the effectiveness of these approaches has been investigated in the area of WSNs. WSN have many applications in different areas and faces many challenging issues such as optimal deployment of nodes, relay node placements, localization of nodes, coverage and connectivity, clustering, routing, data aggregation, cross-layer design, and fault tolerance. Most of these issues have been resolved by the meta-heuristic approaches with developing a new strategy. Still it is required to develop new algorithms with using the best features of meta-heuristic techniques. This work focuses on the optimal coverage-aware deployment, localization, coverage aware clustering, routing, relay node placement and cross layer design methods based on meta-heuristic algorithms. And, provide a discussion about the comparative performance evaluation of these techniques.