The target tracking issue has always been the hotspot in wireless sensor network, and with the emergence of new application in multimedia and real-time transmission, new requirements are proposed for transmission performance of target tracking routing; therefore, a software-defined network–based hierarchical adaptive routing algorithm of wireless sensor network is proposed in this article. The algorithm takes into account both network energy and throughput, uses Hopfield neural network algorithm to calculate the optimal path among adjacent clusters as a local routing (LR), and builds the Multi-choice Knapsack Problem model based on local paths to realize end-to-end global routing, in order to realize the routing of tracking target information under multi-objective conditions. The test bed includes physical and simulation tests. Experimental results show that the proposed algorithm is superior to low energy adaptive clustering hierarchy (LEACH) and Sequential Assignment Routing under different test scenarios.
Conservation of Energy in Wireless Sensor Network by Preventing Denial of Sleep Attack
