Optimization of energy-efficient dynamic task assignment for wireless sensor networks based on particle swarm algorithm

Abstract

This paper provides an in-depth analysis of the optimization of energy-efficient dynamic task allocation in wireless sensor networks through an improved particle swarm optimization algorithm, and introduces the idea of software-defined networking into wireless sensor network to propose a software-defined wireless sensor network non-uniform cluster routing protocol. The protocol decouples the data layer from the control layer, and the base station performs the cluster head election, network clustering, and routing control operations. The base station optimizes the cluster head election process by electing cluster head nodes using an improved particle cluster algorithm. Based on the elected cluster head nodes, the base station calculates their corresponding contention radius and plans the data transmission path. The results of the calculation are sent to the corresponding nodes for cluster creation and data transmission. The simulation results fully show that the use of this protocol can achieve the purpose of significantly extending the service life of the network. This paper comprehensively analyses the whole process of mobile charging of UAVs under improved conditions and proposes a path planning algorithm. The multi-level weighted charging path planning proposed in this paper considers both fairness and timeliness. Finally, the paper verifies the effectiveness of the algorithm.