{"title":"An incentive-based quality of service aware algorithm for offline inter-AS traffic engineering","authors":"Kin-ho Ho, G. Pavlou, M. Howarth, Ning Wang","doi":"10.1109/IPOM.2004.1547589","DOIUrl":null,"url":null,"abstract":"This paper focuses on incentive-based offline inter-AS traffic engineering with end-to-end quality of service (QoS) guarantees. We investigate a key inter-AS traffic engineering problem, the \"egress router selection problem\". The objective is to select an egress router for each expected aggregate inter-AS traffic flow so that the required end-to-end QoS is provided and the capacity constraint of each inter-AS link is met while minimizing the total inter-AS transit cost. The problem is NP-hard and we propose a genetic algorithm to solve it. Simulation results show that our proposed approach performs better than conventional greedy-based approaches.","PeriodicalId":197627,"journal":{"name":"2004 IEEE International Workshop on IP Operations and Management","volume":"16 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"11","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2004 IEEE International Workshop on IP Operations and Management","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IPOM.2004.1547589","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 11
Abstract
This paper focuses on incentive-based offline inter-AS traffic engineering with end-to-end quality of service (QoS) guarantees. We investigate a key inter-AS traffic engineering problem, the "egress router selection problem". The objective is to select an egress router for each expected aggregate inter-AS traffic flow so that the required end-to-end QoS is provided and the capacity constraint of each inter-AS link is met while minimizing the total inter-AS transit cost. The problem is NP-hard and we propose a genetic algorithm to solve it. Simulation results show that our proposed approach performs better than conventional greedy-based approaches.