A detection probability guaranteed energy-efficient scheduling mechanism in large-scale WSN

Abstract

In intrusion detection wireless sensor network (WSN), ensuring detection performance and prolonging network lifetime are two equally important but contradictory pursuits. In this paper, we propose a node scheduling scheme jointly considering the detection probability, energy consumption, and energy balance to ensure the detection performance and maximize the network lifetime. We mathematically transform the scheduling process into an optimization problem and further propose a novel mechanism called greedy-like step-by-step trimming heuristic algorithm (GLSTA) to obtain the optimal task nodes set. By gradually trimming unnecessary nodes, GLSTA intelligently eliminates redundancy and obtains a task set that can save energy and balance the residual energy of nodes. Moreover, we propose a dual cluster head (OCH-DCH, organization cluster head-data cluster head) scheme to realize the smooth update of the cluster due to the target movement. Simulation results show that the rounds of half nodes death of GLSTA are extended by at least 28.6% compared with existing mechanisms.