Multi-vehicle Ad-hoc Network Routing Algorithm with Ant and Quantum Particle Swarm Optimization Combined

摘要

In order to improve data transfer efficiency of the vehicle self-organizing networks and reduce end transmission delay, this paper presents a Multi-vehicle ad-hoc network routing algorithm with Ant and quantum particle swarm optimization combined (AQVT). The algorithm based on the thinking of ant colony algorithm that can find the optimal path, through distance relationship between vehicle and roadside access point and vehicle location information to as measures of ant search path, to find the optimal vehicles network routing. and uses the idea of QPSO algorithm that can global search to enhance the global convergence of the algorithm. Experimental results show that, compared MROFDM algorithm and DRIP algorithm, AQVT algorithm can achieve higher data delivery ratio and obtain a lower-end latency.