{"title":"有效的网络监控","authors":"Y. Breitbart, F. Dragan, Hassan Gobjuka","doi":"10.1109/ICCCN.2004.1401682","DOIUrl":null,"url":null,"abstract":"Various network monitoring and performance evaluation schemes generate considerable amount of traffic, which affects network performance. In this paper we describe a method for minimizing network monitoring overhead based on shortest path tree (SPT) protocol. We describe two different variations of the problem: the A-problem and the E-problem, and show that there is a significant difference between them. We prove that finding optimal solutions is NP-hard for both variations, and propose a theoretically best possible heuristic for the A-problem and three different heuristics for the E-problem, one of them being also theoretically best possible. We show that one can compute in polynomial time an O(ln|V|)-approximate solution for each of these problems. Then, we analyze the performance of our heuristics on large graphs generated using Waxman and power-law models as well as on real ISP topology maps. Experiment results show more than 80% improvement when using our heuristics on real topologies over the naive approaches","PeriodicalId":229045,"journal":{"name":"Proceedings. 13th International Conference on Computer Communications and Networks (IEEE Cat. No.04EX969)","volume":"330 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2004-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"20","resultStr":"{\"title\":\"Effective network monitoring\",\"authors\":\"Y. Breitbart, F. Dragan, Hassan Gobjuka\",\"doi\":\"10.1109/ICCCN.2004.1401682\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Various network monitoring and performance evaluation schemes generate considerable amount of traffic, which affects network performance. In this paper we describe a method for minimizing network monitoring overhead based on shortest path tree (SPT) protocol. We describe two different variations of the problem: the A-problem and the E-problem, and show that there is a significant difference between them. We prove that finding optimal solutions is NP-hard for both variations, and propose a theoretically best possible heuristic for the A-problem and three different heuristics for the E-problem, one of them being also theoretically best possible. We show that one can compute in polynomial time an O(ln|V|)-approximate solution for each of these problems. Then, we analyze the performance of our heuristics on large graphs generated using Waxman and power-law models as well as on real ISP topology maps. Experiment results show more than 80% improvement when using our heuristics on real topologies over the naive approaches\",\"PeriodicalId\":229045,\"journal\":{\"name\":\"Proceedings. 13th International Conference on Computer Communications and Networks (IEEE Cat. No.04EX969)\",\"volume\":\"330 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2004-10-11\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"20\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings. 13th International Conference on Computer Communications and Networks (IEEE Cat. No.04EX969)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCCN.2004.1401682\",\"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. 13th International Conference on Computer Communications and Networks (IEEE Cat. No.04EX969)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCCN.2004.1401682","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Various network monitoring and performance evaluation schemes generate considerable amount of traffic, which affects network performance. In this paper we describe a method for minimizing network monitoring overhead based on shortest path tree (SPT) protocol. We describe two different variations of the problem: the A-problem and the E-problem, and show that there is a significant difference between them. We prove that finding optimal solutions is NP-hard for both variations, and propose a theoretically best possible heuristic for the A-problem and three different heuristics for the E-problem, one of them being also theoretically best possible. We show that one can compute in polynomial time an O(ln|V|)-approximate solution for each of these problems. Then, we analyze the performance of our heuristics on large graphs generated using Waxman and power-law models as well as on real ISP topology maps. Experiment results show more than 80% improvement when using our heuristics on real topologies over the naive approaches