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Ant colony optimization algorithm based P2P system replica optimal location strategy

机译:基于蚁群优化算法的P2P系统副本最优定位策略

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This paper presents a new replica optimal location strategy based on ant colony optimization algorithm. Through the improvement of ant algorithm, it can effectively choose the optimal replica node from a great number of nodes in Peer-to-Peer (P2P) system, which will help to realize the global optimization. The strategy fully considers that P2P nodes are heterogeneous, so the replica of a high degree of popularity will be placed in the high-performance nodes. It increases the high availability of the popular files. At the same time, owing to the increase of the high popular replica, it reduces the number of inquiring nodes when searching a file and decreasing the network traffic. This strategy also takes full consideration of the deferent factors that affect replica location, like path load, delay and so on. The simulation by using P2P tool PeerSim show that this strategy can effectively reduce request response time. Therefore, it improves performance of overall system.
机译:本文介绍了基于蚁群优化算法的新型复制品最优定位策略。通过改进蚂蚁算法,它可以有效地从点对点(P2P)系统中的大量节点中选择最佳副本节点,这将有助于实现全局优化。该策略充分考虑了P2P节点是异构的,因此高级普及度的复制品将放置在高性能节点中。它增加了流行文件的高可用性。同时,由于高流行的副本的增加,它在搜索文件时减少了查询节点的数量并减少了网络流量。此策略还充分考虑了影响副本位置的延期因素,如路径负载,延迟等。使用P2P工具Peersim的仿真表明,该策略可以有效地减少请求响应时间。因此,它提高了整个系统的性能。

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