{"title":"A counterexample in congestion control of wireless networks","authors":"V. Raghunathan, P. Kumar","doi":"10.1145/1089444.1089496","DOIUrl":null,"url":null,"abstract":"One of the triumphs of wireline network research of the last decade has been the casting of the Internet congestion control problem within an optimization framework based on utility functions. Such an approach provides a sound understanding of the underlying stability and fairness issues, as well as a post-facto justification of TCP-like additive-increase multiplicative-decrease (AIMD) algorithms. This paper provides a counter-example showing that the same result cannot be extended to wireless networks, at least not in a straightforward manner.The fundamental difference is that wireless networks are of a broadcast nature. There is no strict notion of a \"link,\" since transmissions from nearby nodes interfere with each other. Using a simple model of interference in wireless networks, a counter-example of a wireless network is presented in which the congestion control mechanism has an unstable equilibrium point at the desired fair solution. Further, ns-2 simulations of this counter-example manifest an oscillatory behavior. Surprisingly, this oscillatory behavior appears to be fairly typical in wireless networks, with most randomly chosen network examples manifesting it. This loss of stability suggests a possible need for the re-design of wireless TCP and wireless queue management to explicitly account for the wireless nature of the effects of interference. wireless interference can make this mechanism unstable. We present counter-example wireless graphs and flow patterns in which the congestion control mechanism fails to remain stable. ns-2 simulations indicate that this loss of stability manifests in practice as oscillatory behavior. Moreover, this oscillatory behavior is fairly typical in wireless networks. This loss of stability suggests a need for the re-design of wireless TCP and wireless queue management to explicitly account for the effects of interference.","PeriodicalId":19766,"journal":{"name":"Perform. Evaluation","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2005-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"43","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Perform. Evaluation","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/1089444.1089496","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 43
Abstract
One of the triumphs of wireline network research of the last decade has been the casting of the Internet congestion control problem within an optimization framework based on utility functions. Such an approach provides a sound understanding of the underlying stability and fairness issues, as well as a post-facto justification of TCP-like additive-increase multiplicative-decrease (AIMD) algorithms. This paper provides a counter-example showing that the same result cannot be extended to wireless networks, at least not in a straightforward manner.The fundamental difference is that wireless networks are of a broadcast nature. There is no strict notion of a "link," since transmissions from nearby nodes interfere with each other. Using a simple model of interference in wireless networks, a counter-example of a wireless network is presented in which the congestion control mechanism has an unstable equilibrium point at the desired fair solution. Further, ns-2 simulations of this counter-example manifest an oscillatory behavior. Surprisingly, this oscillatory behavior appears to be fairly typical in wireless networks, with most randomly chosen network examples manifesting it. This loss of stability suggests a possible need for the re-design of wireless TCP and wireless queue management to explicitly account for the wireless nature of the effects of interference. wireless interference can make this mechanism unstable. We present counter-example wireless graphs and flow patterns in which the congestion control mechanism fails to remain stable. ns-2 simulations indicate that this loss of stability manifests in practice as oscillatory behavior. Moreover, this oscillatory behavior is fairly typical in wireless networks. This loss of stability suggests a need for the re-design of wireless TCP and wireless queue management to explicitly account for the effects of interference.