Alzilal Kamal Algezoly, F. Abdulrazzak, Sharaf A. Alhomdy
{"title":"OpenFlow Protocol Based on UserSpace (OFUS)","authors":"Alzilal Kamal Algezoly, F. Abdulrazzak, Sharaf A. Alhomdy","doi":"10.1109/ICOICE48418.2019.9035186","DOIUrl":null,"url":null,"abstract":"In recent years, there is a general tendency in the field of networking to use programmable networks. One of the most important types of networks that have gained more attention is the Software Defined Networks (SDN), which is based on the principle of separation between the control plane and the data plane. This in turn made the network control centralized and programmable through a centralized controller that is managed by a protocol called OpenFlow. When the main OpenFlow protocol is used, the challenge of time usage in the process of creating communication channels becomes evident each time packets are transmitted. Therefore, this research intends to propose an enhanced algorithm to improve the network performance by integrating the idea of userspace that was successful with operating systems and activating it within SDN networks. The proposed OpenFlow based on UserSpace (OFUS) has been analyzed and compared to the OpenFlow-enabled SDN networks in terms of Round Trip Time (RTT) and the network throughput as performance measurements. The comparative analysis was made by using the open-source Mininet network simulator. The comparative analysis done by using open-source Mininet network simulator on four types of topologies. The results of the enhanced algorithm OFUS showed that the performance of the network has been improved for the RTT and throughput compare to OpenFlow-enabled networks. The RTT in single, linear, tree and custom topologies are 40.3%, 36.2%, 51% and 20.4% whereas throughput 65.4%, 57%, 104.2% and 25.6% respectively.","PeriodicalId":109414,"journal":{"name":"2019 First International Conference of Intelligent Computing and Engineering (ICOICE)","volume":"142 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 First International Conference of Intelligent Computing and Engineering (ICOICE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICOICE48418.2019.9035186","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
In recent years, there is a general tendency in the field of networking to use programmable networks. One of the most important types of networks that have gained more attention is the Software Defined Networks (SDN), which is based on the principle of separation between the control plane and the data plane. This in turn made the network control centralized and programmable through a centralized controller that is managed by a protocol called OpenFlow. When the main OpenFlow protocol is used, the challenge of time usage in the process of creating communication channels becomes evident each time packets are transmitted. Therefore, this research intends to propose an enhanced algorithm to improve the network performance by integrating the idea of userspace that was successful with operating systems and activating it within SDN networks. The proposed OpenFlow based on UserSpace (OFUS) has been analyzed and compared to the OpenFlow-enabled SDN networks in terms of Round Trip Time (RTT) and the network throughput as performance measurements. The comparative analysis was made by using the open-source Mininet network simulator. The comparative analysis done by using open-source Mininet network simulator on four types of topologies. The results of the enhanced algorithm OFUS showed that the performance of the network has been improved for the RTT and throughput compare to OpenFlow-enabled networks. The RTT in single, linear, tree and custom topologies are 40.3%, 36.2%, 51% and 20.4% whereas throughput 65.4%, 57%, 104.2% and 25.6% respectively.