{"title":"CherryPick: tracing packet trajectory in software-defined datacenter networks","authors":"Praveen Tammana, R. Agarwal, Myungjin Lee","doi":"10.1145/2774993.2775066","DOIUrl":null,"url":null,"abstract":"SDN-enabled datacenter network management and debugging can benefit by the ability to trace packet trajectories. For example, such a functionality allows measuring traffic matrix, detecting traffic anomalies, localizing network faults, etc. Existing techniques for tracing packet trajectories require either large data collection overhead or large amount of data plane resources such as switch flow rules and packet header space. We present CherryPick, a scalable, yet simple technique for tracing packet trajectories. The core idea of our technique is to cherry-pick the links that are key to representing an end-to-end path of a packet, and to embed them into its header on its way to destination. Preliminary evaluation on a fat-tree topology shows that CherryPick requires minimal switch flow rules, while using header space close to state-of-the-art techniques.","PeriodicalId":316190,"journal":{"name":"Proceedings of the 1st ACM SIGCOMM Symposium on Software Defined Networking Research","volume":"106 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"66","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 1st ACM SIGCOMM Symposium on Software Defined Networking Research","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2774993.2775066","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 66
Abstract
SDN-enabled datacenter network management and debugging can benefit by the ability to trace packet trajectories. For example, such a functionality allows measuring traffic matrix, detecting traffic anomalies, localizing network faults, etc. Existing techniques for tracing packet trajectories require either large data collection overhead or large amount of data plane resources such as switch flow rules and packet header space. We present CherryPick, a scalable, yet simple technique for tracing packet trajectories. The core idea of our technique is to cherry-pick the links that are key to representing an end-to-end path of a packet, and to embed them into its header on its way to destination. Preliminary evaluation on a fat-tree topology shows that CherryPick requires minimal switch flow rules, while using header space close to state-of-the-art techniques.