基于能量感知路由和优化算法的SDN动态负载均衡

Javesh Dafda, Mansi Subhedar
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引用次数: 1

摘要

在软件定义网络中,负载均衡是将流量数据包从源端移动到目的端的关键管理操作。在现有工程中,采用蚁群优化(蚁群优化)和动态负载均衡来提高SDN的性能。为了改善理想路径的搜索、响应时间、跨越时间和能量消耗,本文提出将能量感知路由与遗传算法(GA)和蚁群负载均衡相结合。目标是在保持用户流服务质量的同时最大限度地减少能源消耗,并实现链路负载平衡。仿真结果表明,该方案在响应时间和能耗方面具有较好的性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Dynamic Load balancing in SDN using Energy Aware Routing and Optimization Algorithm
In software defined networking, load balancing is a crucial management operation for moving traffic packets from source to destination. Ant Colony Optimization (ACO) was employed with dynamic load balancing to enhance SDN performance in existing works. In order to improve the search for the ideal path, response time, span-time, and energy consumption, it is proposed in this article to employ energy-aware routing with a Genetic Algorithm (GA) and ACO load balancing. The goals are to minimize energy consumption while maintaining a quality of service for user flows and to achieve link load balancing. Simulation results demonstrate that the proposed scheme performs better in terms of response time and energy consumption.
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