AKself-adaptive SDNcontroller placement for wide area networks Project supported by the National Natural Science Foundation of China (Nos. 61432002, 61370199, 61370198, 61300187, and 61402069), the Fundamental Research Funds for the Central Universities, China (Nos. DUT15QY20, DUT15TD29, and 3132016029), and the Prospective Research Project on Future Networks from Jiangsu Future Networks Innovation Institute, China A preliminary version was presented at the IEEE/CIC International Conference on Communications in China, Shanghai, China, Oct. 13–15, 2014
Peng XIAO, Zhi-yang LI, Song GUO, Heng QI, Wen-yu QU, Hai-sheng YU
AKself-adaptive SDNcontroller placement for wide area networks Project supported by the National Natural Science Foundation of China (Nos. 61432002, 61370199, 61370198, 61300187, and 61402069), the Fundamental Research Funds for the Central Universities, China (Nos. DUT15QY20, DUT15TD29, and 3132016029), and the Prospective Research Project on Future Networks from Jiangsu Future Networks Innovation Institute, China A preliminary version was presented at the IEEE/CIC International Conference on Communications in China, Shanghai, China, Oct. 13–15, 2014
As a novel architecture, software-defined networking (SDN) is viewed as the key technology of future networking. The core idea of SDN is to decouple the control plane and the data plane, enabling centralized, flexible, and programmable network control. Although local area networks like data center networks have benefited from SDN, it is still a problem to deploy SDN in wide area networks (WANs) or large-scale networks. Existing works show that multiple controllers are required in WANs with each covering one small SDN domain. However, the problems of SDN domain partition and controller placement should be further addressed. Therefore, we propose the spectral clustering based partition and placement algorithms, by which we can partition a large network into several small SDN domains efficiently and effectively. In our algorithms, the matrix perturbation theory and eigengap are used to discover the stability of SDN domains and decide the optimal number of SDN domains automatically. To evaluate our algorithms, we develop a new experimental framework with the Internet2 topology and other available WAN topologies. The results show the effectiveness of our algorithm for the SDN domain partition and controller placement problems.
Software-defined networking (SDN) / Controller placement / K self-adaptive method
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