基于联盟博弈的自适应SDN交换机迁移机制

doi:10.11959/j.issn.1000-436x.2020161

通信学报 ›› 2020, Vol. 41 ›› Issue (8): 1-10.doi: 10.11959/j.issn.1000-436x.2020161

• 学术论文 • 下一篇

基于联盟博弈的自适应SDN交换机迁移机制

姚蓝,兰巨龙

国家数字交换系统工程技术研究中心，河南郑州 450001

修回日期:2020-06-30 出版日期:2020-08-25 发布日期:2020-09-05
作者简介:姚蓝（1982- ），女，河南信阳人，国家数字交换系统工程技术研究中心博士生，主要研究方向为软件定义网络|兰巨龙（1962- ），男，河北张家口人，博士，国家数字交换系统工程技术研究中心教授、博士生导师，主要研究方向为未来信息通信网络关键理论与技术
基金资助:
国家自然科学基金资助项目(61521003);国家自然科学基金资助项目(61872382);国家重点研发计划基金资助项目(2017YFB0803204);广东省重点邻域研发计划基金资助项目(2018B010113001)

Adaptive SDN switch migration mechanism based on coalitional game

Lan YAO,Julong LAN

National Digital Switching System Engineering ＆Research Center,Zhengzhou 450001,China

Revised:2020-06-30 Online:2020-08-25 Published:2020-09-05
Supported by:
The National Natural Science Foundation of China(61521003);The National Natural Science Foundation of China(61872382);The National Key Research and Development Program of China(2017YFB0803204);The Research and Development Program in Key Areas of Guangdong Province(2018B010113001)

摘要/Abstract

摘要：

针对软件定义网络（SDN）中不合理的控制器和交换机映射关系导致的控制平面性能低的问题，提出基于联盟博弈的自适应交换机迁移机制。首先，综合考虑控制器资源利用率、控制开销和流建立时间，将交换机迁移问题建模为组合优化问题；然后引入博弈论设计分布式算法，每个控制器独立运行控制逻辑，通过控制器之间协调合作、联盟博弈，实现了依据流量特征的自适应交换机迁移。仿真结果表明，所提机制能更好地适应流量特征，减少约19%的控制流量开销和30%的平均流建立时间，提高了控制器资源利用率。

关键词: 软件定义网络, 交换机迁移, 联盟博弈, 资源利用率

Abstract:

The problem of poor control plane performance causes in software-defined Networking due to the unreasonable mapping relationship between controllers and switches.To address this issue,an adaptive switch migration mechanism based on coalitional game was proposed.First,comprehensively considering the controller resource utilization,control overhead,and flow establishment time,the switch migration problem was modeled as a combination optimization problem.Then,a game theory was introduced to design a distributed algorithm,where each controller ran control logic independently and implemented coalitional game between controllers to achieve an adaptive switch migration mechanism that adapted to traffic characteristics.The simulation results show that the proposed mechanism can better adapt to the flow characteristics,reduce the control traffic overhead by about 19% and the average flow settling time by 30%,and improve the controller resource utilization.

Key words: software-defined networking, switch migration, coalitional game, resource utilization

中图分类号:

TP393.2

姚蓝,兰巨龙. 基于联盟博弈的自适应SDN交换机迁移机制[J]. 通信学报, 2020, 41(8): 1-10.

Lan YAO,Julong LAN. Adaptive SDN switch migration mechanism based on coalitional game[J]. Journal on Communications, 2020, 41(8): 1-10.

图/表 10

图1

图2

图3

图4

图5

图6

表1

图7

图8

图9

参考文献 26

[1]	NUNES B A A , MENDONCA M , NGUYEN X N ,et al. A survey of software-defined networking:past,present,and future of programmable networks[J]. IEEE Communications Surveys ＆ Tutorials, 2014,16(3): 1617-1634.
[2]	ZHANG Y , CUI L , WANG W ,et al. A survey on software defined networking with multiple controllers[J]. Journal of Network and Computer Applications, 2017,103: 101-118.
[3]	胡涛, 张建辉, 孔维功 ,等. SDN 中基于过程优化的交换机竞争迁移算法[J]. 通信学报, 2017,38(8): 213-222.
	HU T , ZHANG J H , KONG W G ,et al. Switch competing migrationalgorithm based on process optimization in SDN[J]. Journal on Communications, 2017,38(8): 213-222.
[4]	DIXIT A , HAO F , MUKHERJEE S ,et al. Towards an elastic distributed SDN controller[J]. Computer Communication Review, 2013,43(4): 7-12.
[5]	KARAKUS M , DURRESI A . A survey:control plane scalability issues and approaches in software-defined networking (SDN)[J]. Computer Networks, 2017,112(15): 279-293.
[6]	ZHOU N , HU T , HU Y X ,et al. An adaptive switch migration strategy for balancing loads in software-defined networking[J]. Application of Electronic Technique, 2019,12: 91-95.
[7]	TOOTOONCHIAN A , GANJALI Y . HyperFlow:a distributed control plane for OpenFlow[C]// Proceedings of the 2010 Internet Network Management Conference on Research on Enterprise Networking. Berkeley:USENIX Association, 2010: 1-14.
[8]	TEEMU K , MARTIN C , NATASHA G ,et al. Onix:a distributed control platform for large-scale production networks[C]// Proceedings of the 9th USENIX Conference on Operating Systems Design and Implementation. Berkeley:USENIX Association, 2010: 1-15.
[9]	BERDE P , HART J . ONOS:towards an open,distributed SDN OS[C]// ACM SIGCOMM Workshop on Hot Topics in Software Defined Networking (HotSDN’14). New York:ACM Press, 2014: 1-6.
[10]	ZHANG J H , HU T , ZHAO W . DDS:distributed decision strategy based on switch migration towards SDN control plane[C]// 2017 International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery. Piscataway:IEEE Press, 2017: 486-493.
[11]	胡涛, 张建辉, 孔维功 ,等. SDN 中基于双向匹配的多控制器动态部署算法[J]. 通信学报, 2018,39(1): 159-169.
	HU T , ZHANG J H , KONG W G ,et al. Dynamic deployment algorithm for multi-controllers based on bidirectional matching in software defined networking[J]. Journal on Communications, 2018,39(1): 159-169.
[12]	XIAO H , HU B , ZHOU L ,et al. DMSSM:a decision-making scheme of switch migration for SDN control plane[C]// IEEE 7th International Conference on Computer Science and Network Technology. Piscataway:IEEE Press, 2019: 348-352.
[13]	XU Y , CELLO M , WANG I ,et al. Walid dynamic switch migration in distributed software-defined networks to achieve controller load balance[J]. IEEE Journal on Selected Areas in Communications, 2019,37(3): 515-529.
[14]	MYKOLA B , ANDRII P , OLEKSIY P.et al . Dynamic switch migration method based on QoE-aware priority marking for intent-based networking[C]// 15th International Conference on Advanced Trends in Radioelecrtronics,Telecommunications and Computer Engineering. Piscataway:IEEE Press, 2020: 864-868.
[15]	BARI M F , ROY A R , CHOWDHURY S R ,et al. Dynamic controller provisioning in software defined networks[C]// Proceedings of the 9th International Conference on Network and Service Management. Piscataway:IEEE Press, 2013: 18-25.
[16]	ZHOU Y , ZHENG K , NI W ,et al. Elastic switch migration for control plane load balancing in SDN[J]. IEEE Access, 2018,6: 3909-3919.
[17]	WANG C , HU B , CHEN S Z ,et al. A switch migration-based decision-making scheme for balancing load in SDN[J]. IEEE Access, 2018,5: 4537-4544.
[18]	GRKEMLI B , PARLAKK A M , CIVANLAR S ,et al. Dynamic management of control plane performance in software-defined networks[C]// In 2016 IEEE NetSoft Conference and Workshops. Piscataway:IEEE Press, 2016: 68-72.
[19]	LI Z Y , HU Y X , HU T ,et al. Dynamic SDN controller association mechanism based on flow characteristics[J]. IEEE Access, 2019,7: 92661-92671.
[20]	CHENG G , CHEN H , HU H ,et al. Dynamic switch migration towards a scalable SDN control plane[J]. International Journal of Communication Systems, 2016,29(9): 1482-1499.
[21]	FILALI A , CHERKAOUI S , KOBBANE A ,et al. Prediction-based switch migration scheduling for SDN load balancing[C]// 2019 IEEE International Conference on Communications. Piscataway:IEEE Press, 2019: 197-210.
[22]	ASADOLLAHI S , GOSWAMI B , SAMEER M ,et al. RYU controller’s scalability experiment on software defined networks[C]// IEEE International Conference on Current Trends in Advanced Computing. Piscataway:IEEE Press, 2018: 1-5.
[23]	PAL C , VEENA S , RUSTAGI R P ,et al. Implementation of simplified custom topology framework in Mininet[C]// 2014 Asia-Pacific Conference on Computer Aided System Engineering.[S.n.:s.l]. 2014: 48-53.
[24]	KNIGHT S , NGUYEN H X , FALKNER N ,et al. The Internet topology zoo[J]. IEEE Journal on Selected Areas in Communications, 2011,29(9): 1765-1775.
[25]	WANG G , ZHAO Y , HUANG J ,et al. A K-means-based network partition algorithm for controller placement in software defined network[C]// 2016 IEEE International Conference on Communications. Piscataway:IEEE Press, 2016: 46-52.
[26]	YAO G , BI J , LI Y ,et al. On the capacitated controller placement problem in software defined networks[J]. IEEE Communications Letters, 2014,18(8): 1339-1342.

网络拓扑	节点数/个	链路数/条	控制器数/个
OS3E	34	42	4
Germany50	50	88	5
Interllifiber	73	93	6
Interoute	110	149	7

基于联盟博弈的自适应SDN交换机迁移机制

Adaptive SDN switch migration mechanism based on coalitional game

在线阅读

PDF下载

可视化

摘要/Abstract

引用本文

使用本文

图/表 10

参考文献 26

相关文章 15

Metrics

推荐阅读 0

[1]	王东滨, 吴东哲, 智慧, 郭昆, 张勖, 时金桥, 张宇, 陆月明. 软件定义网络抗拒绝服务攻击的流表溢出防护[J]. 通信学报, 2023, 44(2): 1-11.
[2]	沙宗轩, 霍如, 孙闯, 汪硕, 黄韬. 基于深度强化学习的转发效能感知流量调度算法[J]. 通信学报, 2022, 43(8): 30-40.
[3]	燕昺昊, 刘勤让, 沈剑良, 汤先拓, 梁栋. 软件定义网络中一种快速无循环路径迁移策略[J]. 通信学报, 2022, 43(5): 24-35.
[4]	吴平, 常朝稳, 左志斌, 马莹莹. 基于地址重载的SDN分组转发验证[J]. 通信学报, 2022, 43(3): 88-100.
[5]	李传煌, 陈泱婷, 唐晶晶, 楼佳丽, 谢仁华, 方春涛, 王伟明, 陈超. QL-STCT：一种SDN链路故障智能路由收敛方法[J]. 通信学报, 2022, 43(2): 131-142.
[6]	吴平, 常朝稳, 马莹莹. 基于端址重载的SDN包转发验证[J]. 通信学报, 2021, 42(7): 70-83.
[7]	常朝稳, 金建树, 韩培胜, 祝现威. 基于属性签名标识的SDN数据包转发验证方案[J]. 通信学报, 2021, 42(6): 131-144.
[8]	周启钊, 于俊清, 李冬. SDN控制层泛洪防御机制研究：检测与缓解[J]. 通信学报, 2021, 42(11): 41-53.
[9]	李硕朋, 方娟, 陈肯. 基于SRv6的确定性网络服务共享保护方案[J]. 通信学报, 2021, 42(10): 32-42.
[10]	王耀民,王霞,董易,张松海,施心陵. 基于斐波那契树优化算法的数据中心流量调度策略[J]. 通信学报, 2020, 41(6): 112-127.
[11]	韩珍珍,赵国锋,徐川,周文涛,周洋洋. 基于时延的LEO卫星网络SDN控制器动态放置方法[J]. 通信学报, 2020, 41(3): 126-135.
[12]	赖英旭,蒲叶玮,刘静. 基于最小代价路径的交换机迁移方法研究[J]. 通信学报, 2020, 41(2): 131-142.
[13]	柯文龙,王勇,叶苗,陈俊奇. Ceph云存储网络中一种业务优先级区分的多播流调度方法[J]. 通信学报, 2020, 41(11): 40-51.
[14]	张海波,王子心,贺晓帆. SDN和MEC架构下V2X卸载与资源分配[J]. 通信学报, 2020, 41(1): 114-124.
[15]	董芳,胡宇翔,李鸥. 基于SDN的自组织网络路由框架及构建方法[J]. 通信学报, 2019, 40(9): 33-44.