{"title":"稳健的网络流量与路由方法的知识攻击者","authors":"Vorapong Suppakitpaisarn, Wenkai Dai, Jean-François Baffier","doi":"10.1109/HPSR.2015.7483079","DOIUrl":null,"url":null,"abstract":"Recently, many algorithms are proposed to find a communication flow that is robust against k-edges failures. That flow can be weaker, if attackers can obtain forwarding information in each router. In this paper, we propose an algorithm that find a forwarding algorithm maximizing the remaining flow in that situation. We show that Kishimoto's multiroute flow is a (k + 1)-approximation algorithm for the problem, when the route number is k + 1. When the route number is optimally chosen, we show that the multiroute flow is a 2-approximation algorithm for most of randomly generated graphs. Our experimental results show that our algorithm has 15%-37% better performance than max-flow algorithm.","PeriodicalId":360703,"journal":{"name":"2015 IEEE 16th International Conference on High Performance Switching and Routing (HPSR)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"Robust network flow against attackers with knowledge of routing method\",\"authors\":\"Vorapong Suppakitpaisarn, Wenkai Dai, Jean-François Baffier\",\"doi\":\"10.1109/HPSR.2015.7483079\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Recently, many algorithms are proposed to find a communication flow that is robust against k-edges failures. That flow can be weaker, if attackers can obtain forwarding information in each router. In this paper, we propose an algorithm that find a forwarding algorithm maximizing the remaining flow in that situation. We show that Kishimoto's multiroute flow is a (k + 1)-approximation algorithm for the problem, when the route number is k + 1. When the route number is optimally chosen, we show that the multiroute flow is a 2-approximation algorithm for most of randomly generated graphs. Our experimental results show that our algorithm has 15%-37% better performance than max-flow algorithm.\",\"PeriodicalId\":360703,\"journal\":{\"name\":\"2015 IEEE 16th International Conference on High Performance Switching and Routing (HPSR)\",\"volume\":\"17 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-07-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2015 IEEE 16th International Conference on High Performance Switching and Routing (HPSR)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/HPSR.2015.7483079\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 IEEE 16th International Conference on High Performance Switching and Routing (HPSR)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/HPSR.2015.7483079","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Robust network flow against attackers with knowledge of routing method
Recently, many algorithms are proposed to find a communication flow that is robust against k-edges failures. That flow can be weaker, if attackers can obtain forwarding information in each router. In this paper, we propose an algorithm that find a forwarding algorithm maximizing the remaining flow in that situation. We show that Kishimoto's multiroute flow is a (k + 1)-approximation algorithm for the problem, when the route number is k + 1. When the route number is optimally chosen, we show that the multiroute flow is a 2-approximation algorithm for most of randomly generated graphs. Our experimental results show that our algorithm has 15%-37% better performance than max-flow algorithm.