{"title":"基于估计的自适应流量聚合方法减少软件定义无线网络的控制流量","authors":"Kazuki Mizuyama, Yuzo Taenaka, K. Tsukamoto","doi":"10.1109/PERCOMW.2017.7917589","DOIUrl":null,"url":null,"abstract":"Applying Software Defined Network (SDN) technology to wireless network attracts much attention. Our previous study proposed several channel utilization methods based on SDN/OpenFlow-enabled multi-channel wireless mesh network (WMN). However, since control messages are transmitted with data traffic on a same channel in WMN, it inevitably affects the network capacity. Especially, the amount of control messages for collecting statistical information of each flow (FlowStats) linearly increases in accordance with the number of flows, thereby being the dominant overhead. In this paper, we propose a method that prevents the increase of control traffic while maintaining network performance. Specifically, our proposed method uses statistical information of each interface (PortStats) instead of FlowStats, and handles multiple flows on the interface together. To handle a part of flows, we propose a way to estimate statistical information of individual flow without extra control messages. Finally, we show that the proposed method can maintain good network capacity with less packet losses and less control messages.","PeriodicalId":319638,"journal":{"name":"2017 IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"9","resultStr":"{\"title\":\"Estimation based adaptable Flow Aggregation Method for reducing control traffic on Software Defined wireless Networks\",\"authors\":\"Kazuki Mizuyama, Yuzo Taenaka, K. Tsukamoto\",\"doi\":\"10.1109/PERCOMW.2017.7917589\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Applying Software Defined Network (SDN) technology to wireless network attracts much attention. Our previous study proposed several channel utilization methods based on SDN/OpenFlow-enabled multi-channel wireless mesh network (WMN). However, since control messages are transmitted with data traffic on a same channel in WMN, it inevitably affects the network capacity. Especially, the amount of control messages for collecting statistical information of each flow (FlowStats) linearly increases in accordance with the number of flows, thereby being the dominant overhead. In this paper, we propose a method that prevents the increase of control traffic while maintaining network performance. Specifically, our proposed method uses statistical information of each interface (PortStats) instead of FlowStats, and handles multiple flows on the interface together. To handle a part of flows, we propose a way to estimate statistical information of individual flow without extra control messages. Finally, we show that the proposed method can maintain good network capacity with less packet losses and less control messages.\",\"PeriodicalId\":319638,\"journal\":{\"name\":\"2017 IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops)\",\"volume\":\"4 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-03-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"9\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/PERCOMW.2017.7917589\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/PERCOMW.2017.7917589","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Estimation based adaptable Flow Aggregation Method for reducing control traffic on Software Defined wireless Networks
Applying Software Defined Network (SDN) technology to wireless network attracts much attention. Our previous study proposed several channel utilization methods based on SDN/OpenFlow-enabled multi-channel wireless mesh network (WMN). However, since control messages are transmitted with data traffic on a same channel in WMN, it inevitably affects the network capacity. Especially, the amount of control messages for collecting statistical information of each flow (FlowStats) linearly increases in accordance with the number of flows, thereby being the dominant overhead. In this paper, we propose a method that prevents the increase of control traffic while maintaining network performance. Specifically, our proposed method uses statistical information of each interface (PortStats) instead of FlowStats, and handles multiple flows on the interface together. To handle a part of flows, we propose a way to estimate statistical information of individual flow without extra control messages. Finally, we show that the proposed method can maintain good network capacity with less packet losses and less control messages.