Mobility-Enabled Sustainable Data Collection in Wireless Sensor Networks

Wireless sensor network (WSN) with static sink(s) suffer from the sink hole problem. To deal with the problem, researchers explored the mobility of the sink as a potential solution as it provides significant performance gain. Herein, data collection is performed by the mobile sink (MS) by visiting a certain number of sojourn locations called rendezvous points (RPs) spread across the entire network. However, finding an efficient path for the MS to collect data is an NP-hard problem; and meta-heuristic algorithms are known to provide approximately good solutions as compared to the optimal solution. Many MS tour planning schemes exist based on meta-heuristic algorithms; nevertheless, they leave out the scope for further research as most of them suffer from one or the other limitations. As a result, the obtained path length and energy consumption are not optimized. In this paper, we address the above issue and present a novel and efficient data collection scheme which is based on the Jaya algorithm. It determines an optimum number of RPs such that the MS path length is optimized. The algorithm is associated with an efficient particle encoding scheme and derivation of a fitness function. The simulation results demonstrate and confirm the superior performance of the proposed algorithm with respect to the contesting algorithms in terms of path length, number of RPs, energy consumption, and network lifetime.