{"title":"Resource Allocation in Multi-Radio Multi-Channel Multi-Hop Wireless Networks","authors":"S. Merlin, N. Vaidya, M. Zorzi","doi":"10.1109/INFOCOM.2008.110","DOIUrl":null,"url":null,"abstract":"A joint congestion control, channel allocation and scheduling algorithm for multi-channel multi-interface multi- hop wireless networks is discussed. The goal of maximizing a utility function of the injected traffic, while guaranteeing queue stability, is defined as an optimization problem where the input traffic intensity, channel loads, interface to channel binding and transmission schedules are jointly optimized by a dynamic algorithm. Due to the inherent NP-Hardness of the scheduling problem, a simple centralized heuristic is used to define a lower bound for the performance of the whole optimization algorithm. The behavior of the algorithm for different numbers of channels, interfaces and traffic flows is shown through simulations.","PeriodicalId":447520,"journal":{"name":"IEEE INFOCOM 2008 - The 27th Conference on Computer Communications","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2008-04-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"102","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE INFOCOM 2008 - The 27th Conference on Computer Communications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/INFOCOM.2008.110","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 102
Abstract
A joint congestion control, channel allocation and scheduling algorithm for multi-channel multi-interface multi- hop wireless networks is discussed. The goal of maximizing a utility function of the injected traffic, while guaranteeing queue stability, is defined as an optimization problem where the input traffic intensity, channel loads, interface to channel binding and transmission schedules are jointly optimized by a dynamic algorithm. Due to the inherent NP-Hardness of the scheduling problem, a simple centralized heuristic is used to define a lower bound for the performance of the whole optimization algorithm. The behavior of the algorithm for different numbers of channels, interfaces and traffic flows is shown through simulations.