一种基于遗传算法的大规模网络路由优化技术

Yusuke Noda, B. P. Gautam
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引用次数: 0

摘要

路由优化是互联网服务提供商寻求优化网络性能和流量传递的基本计算机制。为了解决路由优化问题,迄今为止报道了各种类型的路由优化算法。遗传算法(GA)是目前最流行的元启发式组合优化算法之一,已广泛应用于网络路由优化等各种优化问题。在本研究中,我们演示了如何使用遗传算法在给定的95个节点和200条链路的网络中找到指定源和目的地之间的优化网络路径。我们的研究结果表明,在计算挑战和路由优化方面,具有较低突变概率的遗传算法是本研究中减少浪费的搜索空间的综合方法。我们的研究表明,遗传算法是一种有效的替代方法,可以找到最优路由,从而达到理想的网络性能并减少拥塞控制。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Proposal of Large Scale Network Route Optimization Technique Based on Genetic Algorithm
Routing optimization is an essential computational mechanism for Internet service providers seeking to optimize network performance and traffic delivery. In order to address the problems of routing optimization, various types of routing optimization algorithms are reported till date. Genetic algorithm (GA) is one of the most popular meta-heuristic combinatorial optimization algorithms, which has been widely used for various optimization problems including network route optimization. In this study, we demonstrated how to find an optimized network path between designated source and destination in a given network with 95 nodes and 200 links using the GA. Our result shows that the GA with the lower mutation probability for reducing the wasteful search space is a comprehensive approach in this study in terms of computational challenges and routing optimization. Our investigation concludes that the GA is an efficient and alternative method of finding an optimal route so as to achieve the desired network performance and to reduce congestion control.
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