{"title":"实现WLRU算法,提高软件定义网络的可扩展性","authors":"H. Nurwarsito, Aryadna Nareindra","doi":"10.1145/3427423.3427444","DOIUrl":null,"url":null,"abstract":"Packet forwarding in a Software Defined Network (SDN) architecture was conducted by a matching process between packet information with flow entry. Network traffic with multiple IP or MAC addresses will increase the number of flow entry insertion and may result in the flow table on the switch running out of space for new flow entry. Flow table overflow that occurred will decrease network scalability in packet forwarding. This study implemented the Weighted Least Recently Used (WLRU) algorithm in the flow table's entry management process to prevent flow table overflow conditions and reduce the number of repeated insertions for an entry. The implementation was conducted using a single linked list data structure and Snort as a packet monitoring. The entry management implementations using the WLRU algorithm successfully overcame the flow table overflow conditions and improved network scalability by being able to forward up to 402 packets, which means 4 times more than before, that only 97 packets. In trade-off overcame the flow table overflow condition, the WLRU algorithm affected the RTT delay value with a minimum value of 19.54 milliseconds, a maximum value of 1607.40 milliseconds, and an average value 195.72 milliseconds.","PeriodicalId":120194,"journal":{"name":"Proceedings of the 5th International Conference on Sustainable Information Engineering and Technology","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2020-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Implementation of WLRU algorithm to improve scalability in software defined network\",\"authors\":\"H. Nurwarsito, Aryadna Nareindra\",\"doi\":\"10.1145/3427423.3427444\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Packet forwarding in a Software Defined Network (SDN) architecture was conducted by a matching process between packet information with flow entry. Network traffic with multiple IP or MAC addresses will increase the number of flow entry insertion and may result in the flow table on the switch running out of space for new flow entry. Flow table overflow that occurred will decrease network scalability in packet forwarding. This study implemented the Weighted Least Recently Used (WLRU) algorithm in the flow table's entry management process to prevent flow table overflow conditions and reduce the number of repeated insertions for an entry. The implementation was conducted using a single linked list data structure and Snort as a packet monitoring. The entry management implementations using the WLRU algorithm successfully overcame the flow table overflow conditions and improved network scalability by being able to forward up to 402 packets, which means 4 times more than before, that only 97 packets. In trade-off overcame the flow table overflow condition, the WLRU algorithm affected the RTT delay value with a minimum value of 19.54 milliseconds, a maximum value of 1607.40 milliseconds, and an average value 195.72 milliseconds.\",\"PeriodicalId\":120194,\"journal\":{\"name\":\"Proceedings of the 5th International Conference on Sustainable Information Engineering and Technology\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-11-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 5th International Conference on Sustainable Information Engineering and Technology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3427423.3427444\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 5th International Conference on Sustainable Information Engineering and Technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3427423.3427444","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
摘要
在软件定义网络(SDN)架构中,报文转发是通过报文信息与流条目之间的匹配过程来实现的。具有多个IP或MAC地址的网络流量将增加流项插入的数量,并可能导致交换机上的流表没有空间容纳新的流项。流表溢出会降低网络在数据包转发中的可扩展性。本研究在流表的条目管理过程中实现加权最小最近使用(Weighted Least Recently Used, WLRU)算法,以防止流表溢出,减少条目的重复插入次数。该实现是使用单个链表数据结构和Snort作为数据包监视来执行的。使用WLRU算法的条目管理实现成功地克服了流表溢出条件,并通过能够转发多达402个数据包来提高网络的可伸缩性,这意味着比以前(仅97个数据包)增加了4倍。在权衡克服流表溢出情况下,WLRU算法对RTT延迟值的影响最小值为19.54毫秒,最大值为1607.40毫秒,平均值为195.72毫秒。
Implementation of WLRU algorithm to improve scalability in software defined network
Packet forwarding in a Software Defined Network (SDN) architecture was conducted by a matching process between packet information with flow entry. Network traffic with multiple IP or MAC addresses will increase the number of flow entry insertion and may result in the flow table on the switch running out of space for new flow entry. Flow table overflow that occurred will decrease network scalability in packet forwarding. This study implemented the Weighted Least Recently Used (WLRU) algorithm in the flow table's entry management process to prevent flow table overflow conditions and reduce the number of repeated insertions for an entry. The implementation was conducted using a single linked list data structure and Snort as a packet monitoring. The entry management implementations using the WLRU algorithm successfully overcame the flow table overflow conditions and improved network scalability by being able to forward up to 402 packets, which means 4 times more than before, that only 97 packets. In trade-off overcame the flow table overflow condition, the WLRU algorithm affected the RTT delay value with a minimum value of 19.54 milliseconds, a maximum value of 1607.40 milliseconds, and an average value 195.72 milliseconds.