基于SDN的数据中心网络流概率路径选择方法
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摘要
为提高数据中心网络(DCN)的链路带宽利用率和吞吐量,提出一种基于软件定义网络(SDN)的流概率路径选择方法。在最短路径选择方法的基础上,利用SDN控制器对网络流进行分类处理,同时计算每条数据流在调度过程中的带宽占用情况以减少数据链路碎片化,并优化DCN数据流量调度,从而实现网络负载均衡。实验结果表明,该方法能降低网络传输时延,提高链路利用率及负载均衡度。
In order to improve the link bandwidth utilization and throughput of Data Center Network(DCN),a Software Defined Network(SDN) based Flow Probability Path Selection(FPPS) method is proposed.On the basis of the shortest path selection method,the SDN controller is used to classify the network flow,calculate the bandwidth occupation condition of each data flow in the scheduling process.Then,it can reduce the data link fragmentation,optimize the DCN data flow scheduling,and realize the network load balancing.Experimental results show that this method can reduce network transmission delay,improve link utilization and load balance degree.
In order to improve the link bandwidth utilization and throughput of Data Center Network(DCN),a Software Defined Network(SDN) based Flow Probability Path Selection(FPPS) method is proposed.On the basis of the shortest path selection method,the SDN controller is used to classify the network flow,calculate the bandwidth occupation condition of each data flow in the scheduling process.Then,it can reduce the data link fragmentation,optimize the DCN data flow scheduling,and realize the network load balancing.Experimental results show that this method can reduce network transmission delay,improve link utilization and load balance degree.
引文
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[2] MASOUDI R,GHAFFARI A.Software defined networks:a survey[J].Journal of Network and Computer Applications,2016,67(C):1-25.
[3] RANDLES M,LAMB D,TALEB-BENDIAB A.A comparative study into distributed load balancing algorithms for cloud computing[C]//Proceedings of IEEE International Conference on Advanced Information Networking and Applications.Washington D.C.,USA:IEEE Computer Society,2010:551-556.
[4] EGILMEZ H E,GORKEMLI B,TEKALP A M,et al.Scalable video streaming over OpenFlow networks:an optimization framework for QoS routing[C]//Proceedings of IEEE International Conference on Image Processing.Washington D.C.,USA:IEEE Press,2011:2241-2244.
[5] SUBBIAH S,PERUMAL V.Energy-aware network resource allocation in SDN[C]//Proceedings of International Conference on Wireless Communications,Signal Processing and Networking.Washington D.C.,USA:IEEE Press,2016:2071-2075.
[6] LONG H,SHEN Y,GUO M,et al.LABERIO:dynamic load-balanced routing in OpenFlow-enabled networks[C]//Proceedings of IEEE International Conference on Advanced Information Networking and Applications.Washington D.C.,USA:IEEE Press,2013:290-297.
[7] LAN Y L,WANG K,HSU Y H.Dynamic load-balanced path optimization in SDN-based data center networks[C]//Proceedings of International Symposium on Communication Systems,Networks and Digital Signal Processing.Washington D.C.,USA:IEEE Press,2016:1-6.
[8] LI Y,PAN D.OpenFlow based load balancing for fat-tree networks with multipath support[EB/OL].[2018-03-11].http://101.96.10.64/users.cis.fiu.edu/～pand/publications/13icc-yu.pdf.
[9] HAN Y,SEO S S,LI J,et al.Software defined networking-based traffic engineering for data center networks[C]//Proceedings of Network Operations and Management Symposium.Washington D.C.,USA:IEEE Press,2014:1-6.
[10] AL-FARES M,RADHAKRISHNAN S,RAGHAVAN B,et al.Hedera:dynamic flow scheduling for data center networks[C]//Proceedings of the 7th USENIX Conference on Networked Systems Design and Implementation.[S.l.]:USENIX Association,2010:16-19.
[11] CURTIS A R,KIM W,YALAGANDULA P.Mahout:low-overhead datacenter traffic management using end-host-based elephant detection[C]//Proceedings of IEEE INFOCOM’11.Washington D.C.,USA:IEEE Press,2011:1629-1637.
[12] 房亚明.基于SDN的数据中心网络流量调度技术研究[D].合肥:安徽大学,2017.
[13] JIN Y Y.Finding the K shortest loopless paths in a network[J].Management Science,1971,17(11):712-716.
[14] 庄怀东.基于SDN的数据中心网络流量调度与负载均衡研究[D].南京:南京航空航天大学,2016.
[15] Floodlight OpenFlow controller[EB/OL].[2018-03-11].http://www.projectfloodlight.org/floodlight/.
[16] Mininet:an instant virtual network on your laptop(or other PC)[EB/OL].[2018-03-11].http://www.mininet.org/.
[17] VAHDAT A,AL-FARES M,LOUKISSAS A.Scalable com-modity data center network architecture:US8483096[P].2013-07-12.
[18] Wireshark.Go deep[EB/OL].[2018-03-11].https://www.wireshark.org/.
[19] Iperf:the TCP,UDP and SCTP network bandwidth measurement tool[EB/OL].[2018-03-11].https://www.iperf.fr/.
[20] BENSON T,AKELLA A,MALTZ D A.Network traffic characteristics of data centers in the wild[C]//Proceed-ings of ACM SIGCOMM Conference on Internet Measurement.New York,USA:ACM Press,2010:267-280.