Ying Zhang, S. Natarajan, Xin Huang, N. Beheshti, Ravi Manghirmalani
{"title":"A compressive method for maintaining forwarding states in SDN controller","authors":"Ying Zhang, S. Natarajan, Xin Huang, N. Beheshti, Ravi Manghirmalani","doi":"10.1145/2620728.2620759","DOIUrl":null,"url":null,"abstract":"Many controller applications require querying existing flow entries in the switches for improving resilience and optimizing resource utilization. These applications can benefit if the controller maintains a copy of the forwarding tables in its memory. However, a naive approach of simply keeping all the tables may encounter scalability challenges. In this work, we identify the redundancy across the flow tables of all switches in the network. We then propose a model-based compression method to efficiently store the network-wide forwarding states. Our evaluation results on a variety of topologies show up to 98% reduction in size.","PeriodicalId":309136,"journal":{"name":"Proceedings of the third workshop on Hot topics in software defined networking","volume":"84 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"14","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the third workshop on Hot topics in software defined networking","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2620728.2620759","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 14
Abstract
Many controller applications require querying existing flow entries in the switches for improving resilience and optimizing resource utilization. These applications can benefit if the controller maintains a copy of the forwarding tables in its memory. However, a naive approach of simply keeping all the tables may encounter scalability challenges. In this work, we identify the redundancy across the flow tables of all switches in the network. We then propose a model-based compression method to efficiently store the network-wide forwarding states. Our evaluation results on a variety of topologies show up to 98% reduction in size.