{"title":"Dynamic Load balancing in SDN using Energy Aware Routing and Optimization Algorithm","authors":"Javesh Dafda, Mansi Subhedar","doi":"10.1109/IBSSC56953.2022.10037571","DOIUrl":null,"url":null,"abstract":"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.","PeriodicalId":426897,"journal":{"name":"2022 IEEE Bombay Section Signature Conference (IBSSC)","volume":"252 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 IEEE Bombay Section Signature Conference (IBSSC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IBSSC56953.2022.10037571","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
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.
京公网安备 11010802042870号
京ICP备2023020795号-1
分享
求助内容：
应助结果提醒方式：
扫码关注我们
