摘要
软件定义网络(SDN)采用一种控制平面和数据平面分离的网络架构,其控制功能由控制器来实现。由于受到控制器处理能力的限制,在大型的SDN网络中,单一的控制器无法满足全体交换机的控制需要,必须使用多个控制器来处理所有的数据流。由于控制器和交换机之间的时延将显著地影响新流的转发,控制器的合理部署将有效地提高整个网络的性能。通过对网络进行子域划分,在谱聚类的基础上,通过为k-means增加均衡部署的目标函数,提出了在时延和容量限制下负载均衡的SDN网络多控制器部署算法。该算法中引入了一个惩罚函数来防止出现孤立节点。仿真结果表明该算法能均衡地对网络进行划分,使控制器和交换机之间保持较小的网络时延以及使各控制器的负载保持均衡。
Software-defined network (SDN) used a network architecture which separates the control plane and data plane. The control logic of SDN was implemented by the controller. Because controller,s capacity was limited, in large scale SDN networks, single controller can not satisfy the requirement of all switches. Multiple controllers were needed to handle all data flows. By the reason that the latency between controller and switch would significantly affect the forwarding of new data flow, the rational placement of controllers would effectively improve the performance of entire network. By partition the network into multiple sub domains, on the base of spectral clustering, a method that added a balanced deployment object function into k-means was given and a balanced multiple controllers placement algorithm in SDN networks which has the latency and capacity limitations was proposed. In this approach, a penalty function was introduced in the algorithm to avoid isolation nodes appearing. The simulations show that this algorithm can balance partition the net- work, keep the latency between controller and switch small and keep loads balancing between controllers.
作者
覃匡宇
黄传河
王才华
史姣丽
吴笛
陈希
QIN Kuang-yu HUANG Chuan-he WANG Cai-hua SHI Jiao-li WU Di CHEN Xi(State Key Lab of Soi,~ware Engineering, Computer School, Wuhan University, Wuhan 430072, China Collaborative Innovation Center of Geospatial Technology, Wuhan University, Wuhan 430072, China School of Information Science and Technology, Jiujiang University, Jiujiang 332005, China)
出处
《通信学报》
EI
CSCD
北大核心
2016年第11期90-103,共14页
Journal on Communications
基金
国家自然科学基金资助项目(No.61373040
No.61572370)~~
关键词
软件定义网络
控制器部署
最小时延
负载均衡
K-MEANS
谱聚类
software-defined network, controller placement, minimal latency, load balancing, k-means, spectral clustering