Multi-agent itinerary planning based Voronoi dividing and Discrete multi-objective Particle swarm optimization

Abstract

As a software entity that migrates between subsystems, mobile agents (MA) can pass and execute codes for flexible application redistribution tasks, local processing, and collaborative signal and information processing. Recent studies have shown that the agent-based approach is more efficient in data collection and aggregation than the client-based server computing model. We calculate a reasonable area and divide the network into a Voronoi diagram. Each area is composed of a data source node and an intermediate node. The intermediate node is responsible for collecting the data in this area, fusing it, and sending it to the data source node. The optimized particle swarm algorithm is used to adaptively select the data source node to obtain the best path of the MA, Simulation results confirm the effectiveness of the proposed algorithm as well as its performance gain over alternative approaches.