{"title":"面向网络模拟器的可伸缩和现实节点模型","authors":"Stein Kristiansen, T. Plagemann, V. Goebel","doi":"10.1145/2018436.2018498","DOIUrl":null,"url":null,"abstract":"Network simulators typically do not include node models. Our studies show that in networks such as mobile networks, the impact of nodes on performance can be significant. Existing techniques to simulate nodes' are not scalable for network simulations, and require a too large modelling effort to be feasible for network research. In this paper, we propose to capture flexible per-protocol performance profiles from real, running systems using instrumentation and traffic benchmarking techniques. By using the obtained profiles as input into an extended scheduler simulator, the behaviour of the node can be accurately reproduced. Since the processing overhead is represented statistically, we preserve scalability and a low modelling overhead.","PeriodicalId":350796,"journal":{"name":"Proceedings of the ACM SIGCOMM 2011 conference","volume":"41 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-08-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"Towards scalable and realistic node models for network simulators\",\"authors\":\"Stein Kristiansen, T. Plagemann, V. Goebel\",\"doi\":\"10.1145/2018436.2018498\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Network simulators typically do not include node models. Our studies show that in networks such as mobile networks, the impact of nodes on performance can be significant. Existing techniques to simulate nodes' are not scalable for network simulations, and require a too large modelling effort to be feasible for network research. In this paper, we propose to capture flexible per-protocol performance profiles from real, running systems using instrumentation and traffic benchmarking techniques. By using the obtained profiles as input into an extended scheduler simulator, the behaviour of the node can be accurately reproduced. Since the processing overhead is represented statistically, we preserve scalability and a low modelling overhead.\",\"PeriodicalId\":350796,\"journal\":{\"name\":\"Proceedings of the ACM SIGCOMM 2011 conference\",\"volume\":\"41 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2011-08-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the ACM SIGCOMM 2011 conference\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/2018436.2018498\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the ACM SIGCOMM 2011 conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2018436.2018498","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Towards scalable and realistic node models for network simulators
Network simulators typically do not include node models. Our studies show that in networks such as mobile networks, the impact of nodes on performance can be significant. Existing techniques to simulate nodes' are not scalable for network simulations, and require a too large modelling effort to be feasible for network research. In this paper, we propose to capture flexible per-protocol performance profiles from real, running systems using instrumentation and traffic benchmarking techniques. By using the obtained profiles as input into an extended scheduler simulator, the behaviour of the node can be accurately reproduced. Since the processing overhead is represented statistically, we preserve scalability and a low modelling overhead.