计算机科学 ›› 2019, Vol. 46 ›› Issue (6A): 312-316.

• 网络与通信 • 上一篇    下一篇

基于SDN的负载均衡网络控制器算法

窦浩铭, 姜慧, 陈思光   

  1. 南京邮电大学江苏省通信与网络技术工程研究中心 南京210003
  • 出版日期:2019-06-14 发布日期:2019-07-02
  • 通讯作者: 陈思光(1984-),男,博士,副教授,主要研究方向为物联网与信息安全,E-mail:sgchen@njupt.edu.cn(通信作者)。
  • 作者简介:窦浩铭(1993-),男,硕士生,主要研究方向为软件定义网络与物联网,E-mail:shelddhm@163.com;姜 慧(1995-),女,硕士生,主要研究方向为软件定义网络与物联网;
  • 基金资助:
    本文受国家自然科学基金项目(61771258,61772034),江苏省“六大人才高峰”高层次人才项目(XYDXXJS-044),江苏省“333高层次人才培养工程”,南京邮电大学‘1311’人才计划,中国博士后科学基金(面上一等资助)(2018M630590),南京邮电大学国家自然科学基金孵化项目(NY217057,NY218058),江苏省通信与网络技术工程研究中心开放课题重点项目(JSGCZX17011)资助。

SDN-based Network Controller Algorithm for Load Balancing

DOU Hao-ming, JIANG Hui, CHEN Si-guang   

  1. Jiangsu Engineering Research Center of Communication and Network Technology,Nanjing University of Posts and Telecommunications,Nanjing 210003,China
  • Online:2019-06-14 Published:2019-07-02

摘要: 当前网络新兴科技呈井喷式发展势头,这些新兴科技在为人们的生活带来极大便利与乐趣的同时,对网络处理海量数据并兼顾安全性和稳定性也提出了更高的要求。一方面,传统网络架构的处理能力很难满足该要求;另一方面,为获得更高的网络效益而开展流量调度优化的研究也大多停留在链路模块,缺少对服务器模块的关注。在此基础上,针对目前绝大多数流量调度优化算法所存在的不足,提出了额外增加了对服务器模块进行考量的路径-服务器流量调度(Path-Server Traffic Scheduling,PSTS)算法,并基于软件定义网络(Software Defined Network,SDN)范式利用Ryu控制器进行模块化功能实现。实现过程中,通过对链路层面和服务器层面的影响因子(性能指标)进行度量,并引入之前已获取的影响因子信息计算权重,来实现对每条链路和每个服务器的排序和筛选,为最终的最佳流量调度提供支撑。仿真结果表明,在流量负载相同的情况下,相较于目前广泛接受的动态负载均衡(Dynamic Load Balancing,DLB)算法,所提出的PSTS算法可以实现更高的平均带宽利用率和更低的平均传输时延;同时,在负载均衡方面,当网络中有大量数据流时,PSTS算法可以更为有效地将数据流均衡地分配给各个服务器,极大地避免了网络中局部拥塞情况的发生,提高了数据流的处理速度,进而提升了网络的整体性能。

关键词: 负载均衡, 流量调度, 路径-服务器流量调度算法, 软件定义网络

Abstract: Currently,the emerging technologies of network show the booming development trend,which bring great convenience and fun for people’s life.However,they put forward the newer and higher requirements for efficient processing ofbig data withdesired security and reliability.On the one hand,the processing ability of the traditional network is difficult to meet these performance and security requirements;on the other hand,in order to obtain higher network benefits,researches of traffic scheduling optimization almost focuse on considering the link module factor,lacking the consideration of server module.In this paper,aiming at the shortcomings of current existing traffic scheduling optimization algorithms,an optimization algorithm called PSTS (Path-Server Traffic Scheduling) which introduces the additional consideration of server module was proposed.The PSTS algorithm is based on the SDN (Software Defined Network) paradigm and finished the modular function realization by using the Ryu controller.In the implementation process,by means of measuring the impact factors (performance metrics) of link and server levels and introducing impact factors which are obtained previously,the proposed algorithm realizes the sorting and filtering operations on each link and each server by calculating the weights.Meanwhile,the sorting and filtering results providestrong support for the final optimal traffic scheduling.The simulation results show that PSTS algorithm can achieve higher average bandwidth utilization and lower average transmission delay compared with DLB (Dynamic Load Balancing) algorithm when they have the same traffic load.At the same time,the proposed algorithm can effectively distribute the data stream more balanced to each serverwhen the network has a large number of data streams,which indicates that it can avoid the local congestion of network significantly,improve the processing speed of data stream,andfinally enhance the overall performance of the network.

Key words: Load balancing, PSTS algorithm, SDN, Traffic scheduling

中图分类号: 

  • TP393
[1]HEEBUM Y,SEUNGRYONG K,TAEKHO N,et al.Dynamic flow steering IoTmonitoring data in SDN-coordinated IoT-cloud services[C]∥Proceedings of International Conference on Information Networking.New York:IEEE Press,2017:625-627.
[2]BIZANIS N,KUIPERS F A.SDN and virtualization solutions for the Internet of Things:asurvey [J].IEEE Access,2016,4(99):5591-5606.
[3]YU Y,LI D,HUANG Y.SVirt:A substrate-agnostic SDN virtualization architecture for multi-tenant cloud[C]∥Proceedings of the IEEE International Conference on Network Protocols.New York:IEEE Press,2015:313-322.
[4]MCKEOWN N,ANDERSON T,BALAKRISHNAN H,et al. OpenFlow:enabling innovation in campus networks[J].ACM SIGCOMM Computer Communication Review,2016,38:69-74.
[5]LI Y,PAN D.OpenFlowbased load balancing for fat-tree networks with multipath support[C]∥Proceedings of the IEEE International Conference on Communications (ICC).New York:IEEE Press,2013:1-5.
[6]PANG J,XU G,FU X.SDN-based data center networking with collaboration of multipath TCP and segment routing[J].IEEE Access,2017,5:9764-9773.
[7]VEISLLARI R,STOL N,BJORNSTAD S,et al.Scalability analysis of SDN-controlled optical ring MAN with hybrid traffic[C]∥Proceedings of the IEEE International Conference on Communications (ICC).New York:IEEE Press,2014:3283-3288.
[8]CZIVA R,JOUËT S,STAPLETON D,et al.SDN-based virtual machine management for cloud data centers [J].IEEE Transactions on Network and Service Management,2016,13(2):212-225.
[9]ZHANG P,CHEN X,GE Y,et al.A parallel processing and synthesis structure for improving access security and efficiency in SDN environment[J].Chinese Journal of Electronics,2016,25(5):817-823.
[10]WANG Y C,YOU S Y.An efficient route management framework for load balance and overhead reduction in SDN-based data center networks [J].IEEE Transactions on Network and Service Management,2018,15(4):1422-1434.
[11]POLVERINI M,CIANFRANI A,LISTANTI M.The power of SDN to improve the estimation of the ISP traffic matrix through the flow spread concept[J].IEEE Journal on Selected Areas in Communications,2016,34(6):1904-1913.
[12]AKHTAR A M,WANG X,HANZO L.Synergistic spectrum sharing in 5G HetNets:a harmonized SDN-enabled approach [J].IEEE Communications Magazine,2016,54(1):40-47.
[13]WANG T,LIU F,XU H.An efficient online algorithm for dynamic SDN controller assignment in data center networks [J].IEEE/ACM Transactions on Networking,2017,25(5):2788-2801.
[14]ZHANG H,GUO X.SDN-based load balancing strategy for server cluster[C]∥Proceedings of IEEE International Conference on Cloud Computing and Intelligence Systems.New York:IEEE Press,2016:662-667.
[1] 田真真, 蒋维, 郑炳旭, 孟利民.
基于服务器集群的负载均衡优化调度算法
Load Balancing Optimization Scheduling Algorithm Based on Server Cluster
计算机科学, 2022, 49(6A): 639-644. https://doi.org/10.11896/jsjkx.210800071
[2] 高捷, 刘沙, 黄则强, 郑天宇, 刘鑫, 漆锋滨.
基于国产众核处理器的深度神经网络算子加速库优化
Deep Neural Network Operator Acceleration Library Optimization Based on Domestic Many-core Processor
计算机科学, 2022, 49(5): 355-362. https://doi.org/10.11896/jsjkx.210500226
[3] 耿海军, 王威, 尹霞.
基于混合软件定义网络的单节点故障保护方法
Single Node Failure Routing Protection Algorithm Based on Hybrid Software Defined Networks
计算机科学, 2022, 49(2): 329-335. https://doi.org/10.11896/jsjkx.210100051
[4] 谭双杰, 林宝军, 刘迎春, 赵帅.
基于机器学习的分布式星载RTs系统负载调度算法
Load Scheduling Algorithm for Distributed On-board RTs System Based on Machine Learning
计算机科学, 2022, 49(2): 336-341. https://doi.org/10.11896/jsjkx.201200126
[5] 夏中, 向敏, 黄春梅.
基于CHBL的P2P视频监控网络分层管理机制
Hierarchical Management Mechanism of P2P Video Surveillance Network Based on CHBL
计算机科学, 2021, 48(9): 278-285. https://doi.org/10.11896/jsjkx.201200056
[6] 宋海宁, 焦健, 刘永.
高速公路中的移动边缘计算研究
Research on Mobile Edge Computing in Expressway
计算机科学, 2021, 48(6A): 383-386. https://doi.org/10.11896/jsjkx.200900212
[7] 王政, 姜春茂.
一种基于三支决策的云任务调度优化算法
Cloud Task Scheduling Algorithm Based on Three-way Decisions
计算机科学, 2021, 48(6A): 420-426. https://doi.org/10.11896/jsjkx.201000023
[8] 郑增乾, 王锟, 赵涛, 蒋维, 孟利民.
带宽和时延受限的流媒体服务器集群负载均衡机制
Load Balancing Mechanism for Bandwidth and Time-delay Constrained Streaming Media Server Cluster
计算机科学, 2021, 48(6): 261-267. https://doi.org/10.11896/jsjkx.200400131
[9] 董仕.
软件定义网络安全问题研究综述
Survey on Software Defined Networks Security
计算机科学, 2021, 48(3): 295-306. https://doi.org/10.11896/jsjkx.200300119
[10] 姚泽玮, 林嘉雯, 胡俊钦, 陈星.
基于PSO-GA的多边缘负载均衡方法
PSO-GA Based Approach to Multi-edge Load Balancing
计算机科学, 2021, 48(11A): 456-463. https://doi.org/10.11896/jsjkx.210100191
[11] 高明, 周慧颖, 焦海, 应丽莉.
基于加权图的链路映射算法
Link Mapping Algorithm Based on Weighted Graph
计算机科学, 2021, 48(11A): 476-480. https://doi.org/10.11896/jsjkx.201200216
[12] 高雅卓, 刘亚群, 张国敏, 邢长友, 王秀磊.
基于多阶段博弈的虚拟化蜜罐动态部署机制
Multi-stage Game Based Dynamic Deployment Mechanism of Virtualized Honeypots
计算机科学, 2021, 48(10): 294-300. https://doi.org/10.11896/jsjkx.210500071
[13] 杨紫淇, 蔡英, 张皓晨, 范艳芳.
基于负载均衡的VEC服务器联合计算任务卸载方案
Computational Task Offloading Scheme Based on Load Balance for Cooperative VEC Servers
计算机科学, 2021, 48(1): 81-88. https://doi.org/10.11896/jsjkx.200800220
[14] 郭飞雁, 唐兵.
基于用户延迟感知的移动边缘服务器放置方法
Mobile Edge Server Placement Method Based on User Latency-aware
计算机科学, 2021, 48(1): 103-110. https://doi.org/10.11896/jsjkx.200900146
[15] 王国澎, 杨剑新, 尹飞, 蒋生健.
负载均衡的处理器运算资源分配方法
Computing Resources Allocation with Load Balance in Modern Processor
计算机科学, 2020, 47(8): 41-48. https://doi.org/10.11896/jsjkx.191000148
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed   
No Suggested Reading articles found!