An Improved Metaheuristic Algorithm for Mobile and Static Wireless Sensor Network with Adjustable Sensing Range

The possibilities of wireless sensor network (WSN) have been shown in many studies in recent years. A critical research topic among them is certainly how to reduce the power consumption of a WSN to prolong its lifetime. In addition to extending the lifetime of static wireless sensors of a WSN, some recent studies have attempted to add mobile wireless sensors to increase the coverage rate of a WSN. For this reason, this study is aimed to find the optimal deployment of a hybrid mobile and static WSN. In this study, an effective search algorithm is presented to maximize the coverage rate of all the targets while minimizing the energy consumption of the static and mobile sensors. The proposed algorithm is an improved version of search economics for single-objective real-parameter optimization problem (SE-SOP), called self-cutting search economics (SCSE). A new division method is also presented for the SE-based algorithm to divide the solution space into a certain number of subspaces and assign suitable computation resources to these subspaces according to their potentialities. The number of subspaces will be decreased so that particular subspaces are apt to acquire more investments (i.e., searches) due to the combining region method, which is helpful to speedup the convergence process. Simulation results show that the proposed algorithm can find out a better plan of network management than all the other search algorithms compared in this study for the WSN containing static and mobile sensors with adjustable sensing range functionality.