蚁群粒子群混合算法在车载网无线接入点的布局优化

Hybrid ACO and PSO for Wireless Access Points in Vehicular Ad-hoc Network

针对具有拓扑结构多变、受周围事物影响、高速变动等特征导致车载网通信性能不佳的问题,将无线接入点作为提高通信性能的关键辅助点。在保证信号覆盖率的情况下,根据车流量,部署最少无线接入点作为最终目标,利用蚁群和粒子群混合算法(AC-PSO)作为一种搜索策略。将AC-PSO混合算法与PSO算法、ACO算法进行对较以便证明该混合算法的优越性。实验表明,AC-PSO混合算法收敛速度比PSO、ACO更快,也说明了该混合算法在车载网中无线AP布局优化应用的有效性。

Aiming at the problem that the communication performance of vehicular network is poor due to the changeable topology,the influence of surroundings and the high-speed change,the wireless access point is regarded as the key auxiliary point to improve the communication performance.To guaranteeing signal coverage,the minimum wireless access point(AP)is deployed as the goal according to the traffic volume.And the hybrid ant colony and particle swarm optimization algorithm(AC-PSO)is used as the search strategy.In order to verify the performance of the hybrid algorithm,it is compared with the classical particle swarm optimization algorithm and ant colony algorithm.The experiments show that the hybrid algorithm has higher speed.The AC-PSO hybrid algorithm for wireless access point problem in vehicular networks is effective.