一种改进的蚁群算法及其在组播路由问题中的应用

Q4 Engineering

International Journal of Wireless and Mobile Computing Pub Date : 2011-12-01 DOI:10.1504/IJWMC.2011.044116

Zhang Yi, Liu Yan-chun

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引用次数: 6

摘要

本文对蚁群算法进行了改进，并用改进后的算法解决了组播路由问题。改进如下:设计了一种新的优化实现方法，以降低传统蚁群算法中蚂蚁路由的处理成本(带宽、延迟、最小成本)。基于网络路由模型，将候选集合限制在最近的c个点，以减少其他点的计数。我们还在被阻挡的点上使用标记来防止选择这些点。仿真结果表明，与传统算法相比，改进算法的收敛速度有很大提高。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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An improved ant colony optimisation and its application on multicast routing problem

In this paper, some improvements on Ant Colony Optimisation (ACO) are presented and we use the improved algorithm to solve the multicast routing problem. The improvements are given as follows: A novel optimised implementing approach is designed to reduce the processing costs (the bandwidth, delay, mincost) involved with routing of ants in the conventional ACO. Based on the model of network routing, the set of candidates is limited to the nearest c points in order to reduce the counting of other points. And we also use the flags on the blocked points in order to prevent selecting these points. Simulations show that the speed of convergence of the improved algorithm can be enhanced greatly compared with the traditional algorithm.

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来源期刊

International Journal of Wireless and Mobile Computing Computer Science-Computer Science (all)

CiteScore

0.80

自引率

0.00%

发文量

期刊介绍： The explosive growth of wide-area cellular systems and local area wireless networks which promise to make integrated networks a reality, and the development of "wearable" computers and the emergence of "pervasive" computing paradigm, are just the beginning of "The Wireless and Mobile Revolution". The realisation of wireless connectivity is bringing fundamental changes to telecommunications and computing and profoundly affects the way we compute, communicate, and interact. It provides fully distributed and ubiquitous mobile computing and communications, thus bringing an end to the tyranny of geography.