【摘要】 资源搜索是P2P网络应用领域中最为广泛的问题,蚁群算法是受到自然界中真实的蚂蚁集体行为的启发而提出的一种算法。将蚁群算法用于非结构化P2P网络资源搜索中,在广度优先搜索技术(BFS)机制的基础上实现了资源的智能搜索。该算法利用蚁群算法特有的信息素以充分利用历史经验,设置了全局更新规则和局部更新规则来更新蚂蚁寻找到所需资源时经过的路径上的信息素浓度,对蚁群算法中的参数做了相应的修改,并给出了算法的简要描述和基本框架。避免了广度优先搜索技术机制中的消息量过大、网络负载过重的问题,从而提高了系统搜索效率。更多还原

【Abstract】 Resource search is a popular application area of P2P networks and the ant colony algorithm (ACA) is a heuristic approach inspired by the foraging behavior of real ants.This article implemented intelligent search based on Breadth First Search (BFS) and ant colony algorithm (ACA).This paper sets the local updating rule and the global updating rule to update the amount of the pheromone in the edge which is passed by the ant which found the right nodes possessing the required resource, makes some modification of the parameter in ACA, and then gives brief description and basic frame of the algorithm.The algorithm avoids the problem of the large quantities of messages and the network overburden by using the pheromone which is proper to ACA and then it has good performances.更多还原