Journal on Communications ›› 2016, Vol. 37 ›› Issue (11): 90-103.doi: 10.11959/j.issn.1000-436x.2016219

• academic paper • Previous Articles     Next Articles

Balanced multiple controllers placement with latency and capacity bound in software-defined network

Kuang-yu QIN1,2,Chuan-he HUANG1,2(),Cai-hua WANG1,Jiao-li SHI1,2,3,Di WU1,2,Xi CHEN1,2   

  1. 1 State Key Lab of Software Engineering, Computer School, Wuhan University, Wuhan 430072, China
    2 Collaborative Innovation Center of Geospatial Technology, Wuhan University, Wuhan 430072, China
    3 School of Information Science and Technology, Jiujiang University, Jiujiang 332005, China
  • Online:2016-11-25 Published:2016-11-30
  • Supported by:
    The National Natural Science Foundation of China;The National Natural Science Foundation of China

Abstract:

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 han-dle 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 de-ployment object function into k-means was given and a balanced multiple controllers placement algorithm in SDN net-works 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.

Key words: software-defined network, controller placement, minimal latency, load balancing, k-means, spectral clustering

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