A Comparative Study of Meta-Heuristic Algorithms for WSN Deployment Problem in Indoor Environments

The wireless sensor deployment problem is one of the major issues in wireless sensor networks (WSNs). It involves designing the optimal network topology within the deployment area in order to maximize network coverage and lifetime and minimize cost and energy consumption under the connectivity constraint. The WSN deployment problem is a challenging NP-hard combinatorial optimization problem due to a number of factors, including the size and the type of the deployment area, the number of obstacles, and the number of objectives to optimize. Consequently, metaheuristics are assumed to be the most efficient methods to compute the deployment scheme in a reasonable amount of time. In this paper, several well-known metaheuristics have been tested on the problem of WSN deployment in indoor environments. The problem has been formulated as a constrained single objective optimization problem, and the performance of the selected algorithms has been evaluated through experimentation on a set of ten representative indoor architectural scenarios with varying dimensions and obstacles.