Metaheuristics for the deployment problem of WSN: A review

The deployment problem (DP) of a wireless sensor network (WSN) is no doubt a critical issue because the strategies it takes will not only strongly impact the overall performance but also the power consumed by the sensors in such a system. This means that a good solution to the deployment problem (DP) cannot just “enhance its performance,” it can also “save the energy” to prolong the lifetime of a wireless sensor network (WSN). However, finding an optimum solution for most DPs with limited computation resources is still a challenging research problem, especially for the NP-hard optimization problems. Compared to exhaustive search and deterministic algorithms, metaheuristics provides an alternative way to solve these optimization problems, by looking for a near optimal solution using limited computation resources within a reasonable time. Aimed at providing not only a systematic survey of metaheuristics for solving the deployment problem but also a roadmap for researchers working on WSN and metaheuristics to further develop and improve a wireless sensor network system, this paper begins with an overview of WSN and the deployment problem, followed by discussions on metaheuristics and how to use them to solve the DP. Then, a comprehensive comparison between metaheuristics for the DP is given. Finally, open issues and future trends of this field are addressed.