Optimal Speed Allocation in Sink-based Energy Harvesting Wireless Sensor Networks

Unlike the existing sink-based data collection in energy harvesting wireless sensor networks (EH-WSNs) in which the mobile sink maintains a constant speed during its trajectory, the allocation of optimal sink speed can further improve the achievable network throughput. Inspired by this fact, in this paper, we formulate the optimal sink speed allocation problem with the objective of maximizing the network throughput (NTM-OSS) in delay-tolerant EH-WSNs. A mixed integer nonlinear programming (MINLP) optimization model is proposed for NTM-OSS formulation which takes into account the time duration for the acceleration and deceleration of mobile sink. With the sensors' information available in advance, an efficient algorithm named as optimal sink speed allocation (OSSAA) is designed which works based on an iteratively speed updating mechanism and runs by the mobile sink within consecutive time intervals. We show that the proposed algorithm guarantees the convergence to near-optimal solutions and has both time and message complexities of polynomial order in the worst case. The results of conducted simulations reveal that the proposed algorithm improves the network throughput by in average 1.6 x 10(3) data unit and achieves an average of 3.3 % energy saving compared to its competitor.