{"title":"软件定义网络中bug的综合研究","authors":"Ayush Bhardwaj, Zhenyu Zhou, Theophilus A. Benson","doi":"10.1109/DSN48987.2021.00026","DOIUrl":null,"url":null,"abstract":"Software-defined networking (SDN) enables innovative and impressive solutions in the networking domain by decoupling the control plane from the data plane. In an SDN environment, the network control logic for load balancing, routing, and access control is written in software running on a decoupled control plane. As with any software development cycle, the SDN control plane is prone to bugs that impact the network’s performance and availability. Yet, as a community, we lack holistic, in-depth studies of bugs within the SDN ecosystem. A bug taxonomy is one of the most promising ways to lay the foundations required for (1) evaluating and directing emerging research directions on fault detection and recovery, and (2) informing operational practices of network administrators. This paper takes the first step towards laying this foundation by providing a comprehensive study and analysis of over 500 ‘critical’ bugs (including $\\sim 150$ with manual analysis) in three of the most widely-used SDN controllers, i.e., FAUCET, ONOS, and CORD. We create a taxonomy of these SDN bugs, analyze their operational impact, and implications for the developers. We use our taxonomy to analyze the effectiveness and coverage of several prominent SDN fault tolerance and diagnosis techniques. This study is the first of its kind in scale and coverage to the best of our knowledge.","PeriodicalId":222512,"journal":{"name":"2021 51st Annual IEEE/IFIP International Conference on Dependable Systems and Networks (DSN)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"A Comprehensive Study of Bugs in Software Defined Networks\",\"authors\":\"Ayush Bhardwaj, Zhenyu Zhou, Theophilus A. Benson\",\"doi\":\"10.1109/DSN48987.2021.00026\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Software-defined networking (SDN) enables innovative and impressive solutions in the networking domain by decoupling the control plane from the data plane. In an SDN environment, the network control logic for load balancing, routing, and access control is written in software running on a decoupled control plane. As with any software development cycle, the SDN control plane is prone to bugs that impact the network’s performance and availability. Yet, as a community, we lack holistic, in-depth studies of bugs within the SDN ecosystem. A bug taxonomy is one of the most promising ways to lay the foundations required for (1) evaluating and directing emerging research directions on fault detection and recovery, and (2) informing operational practices of network administrators. This paper takes the first step towards laying this foundation by providing a comprehensive study and analysis of over 500 ‘critical’ bugs (including $\\\\sim 150$ with manual analysis) in three of the most widely-used SDN controllers, i.e., FAUCET, ONOS, and CORD. We create a taxonomy of these SDN bugs, analyze their operational impact, and implications for the developers. We use our taxonomy to analyze the effectiveness and coverage of several prominent SDN fault tolerance and diagnosis techniques. This study is the first of its kind in scale and coverage to the best of our knowledge.\",\"PeriodicalId\":222512,\"journal\":{\"name\":\"2021 51st Annual IEEE/IFIP International Conference on Dependable Systems and Networks (DSN)\",\"volume\":\"32 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-06-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 51st Annual IEEE/IFIP International Conference on Dependable Systems and Networks (DSN)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/DSN48987.2021.00026\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 51st Annual IEEE/IFIP International Conference on Dependable Systems and Networks (DSN)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/DSN48987.2021.00026","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A Comprehensive Study of Bugs in Software Defined Networks
Software-defined networking (SDN) enables innovative and impressive solutions in the networking domain by decoupling the control plane from the data plane. In an SDN environment, the network control logic for load balancing, routing, and access control is written in software running on a decoupled control plane. As with any software development cycle, the SDN control plane is prone to bugs that impact the network’s performance and availability. Yet, as a community, we lack holistic, in-depth studies of bugs within the SDN ecosystem. A bug taxonomy is one of the most promising ways to lay the foundations required for (1) evaluating and directing emerging research directions on fault detection and recovery, and (2) informing operational practices of network administrators. This paper takes the first step towards laying this foundation by providing a comprehensive study and analysis of over 500 ‘critical’ bugs (including $\sim 150$ with manual analysis) in three of the most widely-used SDN controllers, i.e., FAUCET, ONOS, and CORD. We create a taxonomy of these SDN bugs, analyze their operational impact, and implications for the developers. We use our taxonomy to analyze the effectiveness and coverage of several prominent SDN fault tolerance and diagnosis techniques. This study is the first of its kind in scale and coverage to the best of our knowledge.