{"title":"Equitable Optimization for Multicast Communication","authors":"Said Fourour, Yahia Lebbah","doi":"10.4018/ijdsst.2020070101","DOIUrl":null,"url":null,"abstract":"Multicast communication is characterized by the multiplicity of streams defining different groups, where each stream has multiple sources. A multicast communication tends to flood the network with a large number of flows that can overload some nodes and unload others. This imbalance in the load distribution weakens network performance and could produce bottlenecks around overloaded nodes. We propose in this article an approach based on a combination of a flow approach and a multi-agent optimization to resolve the load balancing issue of multicast communication. We use ordered weighted average (OWA), a multi-criteria optimization method, to balance the degree of the nodes, ensuring a balanced load distribution across the network. The experiments conducted on a series of networks show that our approach provides a better equitable load assignment.","PeriodicalId":42414,"journal":{"name":"International Journal of Decision Support System Technology","volume":"20 1","pages":"1-25"},"PeriodicalIF":0.6000,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Decision Support System Technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.4018/ijdsst.2020070101","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"COMPUTER SCIENCE, INFORMATION SYSTEMS","Score":null,"Total":0}
引用次数: 3
Abstract
Multicast communication is characterized by the multiplicity of streams defining different groups, where each stream has multiple sources. A multicast communication tends to flood the network with a large number of flows that can overload some nodes and unload others. This imbalance in the load distribution weakens network performance and could produce bottlenecks around overloaded nodes. We propose in this article an approach based on a combination of a flow approach and a multi-agent optimization to resolve the load balancing issue of multicast communication. We use ordered weighted average (OWA), a multi-criteria optimization method, to balance the degree of the nodes, ensuring a balanced load distribution across the network. The experiments conducted on a series of networks show that our approach provides a better equitable load assignment.