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ANT COLONY OPTIMIZATION ROUTING ALGORITHM FOR P2P NETWORKS

机译:P2P网络的蚁群优化路由算法

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摘要

Due to the importance of these information that move through the local and global networks, recent researches focused on improving the speed of communication networks with little attention to have the ability to secure the flow of the transmitted information through them. To tackle into the preceding points, some protocols have been developed in the literature to support efficiently the transfer of encrypted data. The efficiency of these protocols such as used in routing information raised the need to propose an intelligent technique that can merge some of the optimal protocols to gain both the high speed and security of the significant valuable transmitted data. In this article. Swarm intelligence follows the behavior of cooperative ants in order to solve hard static and dynamic optimization problems using Ant Colony Optimization (ACO) technique and an artificial ant colony capable of offending the shortest path source to connected P2P nodes. The main goal of Ant Colony Optimization -based search algorithm is that to achieve well organised information recovery and reduced load overhead.
机译:由于这些信息在本地和全球网络中传播的重要性,因此最近的研究集中在提高通信网络的速度上,而很少注意具有确保通过它们的传输信息流的能力。为了解决上述问题,文献中已经开发了一些协议以有效地支持加密数据的传输。这些协议(例如在路由信息中使用)的效率提高了对提出一种智能技术的需求,该技术可以合并一些最佳协议来获得重要有价值的传输数据的高速性和安全性。在这篇文章中。群智能跟随协作蚂蚁的行为,以便使用蚁群优化(ACO)技术和能够侵害连接的P2P节点的最短路径源的人工蚁群来解决硬静态和动态优化问题。基于蚁群优化的搜索算法的主要目标是实现组织良好的信息恢复并减少负载开销。

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