{"title":"Adaptive and distributed monitoring mechanism in software-defined networks","authors":"X. Phan, I. D. Martinez-Casanueva, K. Fukuda","doi":"10.23919/CNSM.2017.8256003","DOIUrl":null,"url":null,"abstract":"Network traffic monitoring is an important factor to ensure the controllability and manageability of software-defined network (SDN). The current monitoring mechanism of SDN requires switches to request the controller for instructions to install flow entries for every new incoming flow. For finegrained monitoring, which requires many flow entries in switches' flow tables, this mechanism creates a non-trivial delay in the forwarding of switches and overhead in the control channel. Our previous work presented SDN-Mon, a monitoring framework that supports fine-grained monitoring for SDN. In this paper, we discuss the aspect of monitoring the flows in a distributed manner. We believe that a distributed monitoring capability enhances the monitoring scalability for SDN. We propose a mechanism that supports SDN to distribute the monitoring load over multiple switches in the network, in which it prevents flows monitoring duplication and balances the monitoring load over switches in the network. With the proposed mechanism, each switch handles much less monitoring load; and the overhead at switches, the control channel, and the controller caused by the monitoring duplication is eliminated. We implement the proposal and integrate it to SDN-Mon to enable a scalable and distributed monitoring capability in SDN. Experimental results show that the proposed mechanism significantly reduces the amount of monitoring load per switch, while the monitoring load is well balanced over switches in the network, with only an acceptable polling and processing overhead.","PeriodicalId":211611,"journal":{"name":"2017 13th International Conference on Network and Service Management (CNSM)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"9","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 13th International Conference on Network and Service Management (CNSM)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.23919/CNSM.2017.8256003","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 9
Abstract
Network traffic monitoring is an important factor to ensure the controllability and manageability of software-defined network (SDN). The current monitoring mechanism of SDN requires switches to request the controller for instructions to install flow entries for every new incoming flow. For finegrained monitoring, which requires many flow entries in switches' flow tables, this mechanism creates a non-trivial delay in the forwarding of switches and overhead in the control channel. Our previous work presented SDN-Mon, a monitoring framework that supports fine-grained monitoring for SDN. In this paper, we discuss the aspect of monitoring the flows in a distributed manner. We believe that a distributed monitoring capability enhances the monitoring scalability for SDN. We propose a mechanism that supports SDN to distribute the monitoring load over multiple switches in the network, in which it prevents flows monitoring duplication and balances the monitoring load over switches in the network. With the proposed mechanism, each switch handles much less monitoring load; and the overhead at switches, the control channel, and the controller caused by the monitoring duplication is eliminated. We implement the proposal and integrate it to SDN-Mon to enable a scalable and distributed monitoring capability in SDN. Experimental results show that the proposed mechanism significantly reduces the amount of monitoring load per switch, while the monitoring load is well balanced over switches in the network, with only an acceptable polling and processing overhead.