高程ACS:一种适用于无线传感器网络路由的改进蚁群算法

ACSA: An Improved Ant Colony Algorithm for Routing Problems of Wireless Sensor Networks

针对无线传感器网络最短路径路由问题,提出了一种基于高程诱导信息的回退蚁群算法-高程ACS,并对高程定义、算法设计思想和算法实现等进行了论述.高程做为一种基于目的节点和源节点的全局诱导信息,反映了当前节点和目的节点之间的可达性.通过引入高程信息,加快了算法收敛速度;通过蚂蚁回退过程,提高了解的质量.仿真结果表明,高程ACS运算和收敛速度快,解的质量高、稳定性好,适合无线传感器网络应用.

Because of the long calculation time and slow convergence speed, ACS （Ant Colony System） can＇t be used directly in Wireless Sensor Networks （WSN）. We presents an improved ACS algorithm based on Altitude Infomation （AD and Ant Withdrawal （AW）, named ACSA （an improved ACS algorithm with AD, bring forward the concept of AI, and discuss the design, realization, performance evaluations of ACSA. AI is global heuristic information which correlative with source and destination node, represents the possibility of ants traveling from currem node to destination. By using AI, the algorithm can get faster convergence speed; by using AW, the algorithm can increase the probability of ants traveling to destination node, and avoid local optimization. The algorithm simulation illustrates that ACSA can get more stable and robust result, faster calculation and convergence speed than ACS on the shortest path problem of WSN.