Application of an Ant Colony Algorithm Based on Complez Networks in Migration of Mobile Agents
One of the main problems in mobile agent migration is planning out an optimal migration path according to the agent tasks and other restrictions when agents migrate to several other hosts. The Ant Colony Algorithm, which has the characteristic of parallelism, positive feedback and heuristic search, is a new evolutionary algorithm and is extremely suitable to the mobile agent migration problem. But it still has some shortcomings such as slowly speed and stagnation behavior. Complex networks theory is a new kind of theory, which finds that some practical networks have new characters. In order to describe these new characters, some new characteristic measures are introduced, one of which is the nodes degree. Based on the classical Ant Algorithm, the parameter degree is added into the state transfer rules of the Ant Algorithm and a self-adaptive pheromone evaporation rate is proposed, which can accelerate the convergence rate and improve the ability of searching an optimum solution. This improved Ant Colony Algorithm is used to plan out an optimal migration path of mobile agents. The results of contrastive experiments show that the algorithm is superior to other related methods both on the quality of solution and on the convergence rate.
mobile agent Ant Colony Algorithm complez networks
JU Ze-wang WANG Hong
Finance and Economics Department, Weifang College of Education, WeiFang,China,262500 Institute of Information Science and Engineering,ShanDong Normal University,China,250014
国际会议
2009 IEEE International Symposium on IT in Medicine & Education( IEEE 教育与医药信息化国际会议)
济南
英文
821-825
2009-08-14（万方平台首次上网日期，不代表论文的发表时间）