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Multi-Controller Placement Towards SDN Based on Louvain Heuristic Algorithm
Author(s) -
Wen Chen,
Cong Chen,
Xueqin Jiang,
Leijie Liu
Publication year - 2018
Publication title -
ieee access
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.587
H-Index - 127
ISSN - 2169-3536
DOI - 10.1109/access.2018.2867931
Subject(s) - aerospace , bioengineering , communication, networking and broadcast technologies , components, circuits, devices and systems , computing and processing , engineered materials, dielectrics and plasmas , engineering profession , fields, waves and electromagnetics , general topics for engineers , geoscience , nuclear engineering , photonics and electrooptics , power, energy and industry applications , robotics and control systems , signal processing and analysis , transportation
The separation of the forwarding and control planes of software-defined networking brings a lot of flexibility to network management. However, with the increase in network capacity, network structure becomes more and more complicated. The controller placement problem in a large-scale network is still a hard nut to crack because of high complexity and difficulty in the tradeoff between performance. In this paper, a novel approach named community detection controller deployment is proposed. With the aid of theory of complex network analysis, the network topology of the controller to be deployed is regarded as a network composed of multiple communities, and then a suitable position is selected in each community to place the controller, which is capable of avoiding the complexity of global deployment. In order to balance the number of switches managed by the controller in each community, the scale constraint factor is introduced into Louvain heuristic algorithm to limit the number of nodes in each community and balance the differences in the number of nodes among different communities. Distinct from the existing clustering-based approaches, this method can independently identify partitions with community attributes according to the network structure without manual intervention. On the other hand, it can adjust the number of nodes within communities on demand to achieve topological equilibrium partition. Experiments are performed on real network topologies, and corresponding results show that the proposed method is more suitable for networks with plenty of nodes and can effectively balance the controllers’ load while keeping latency at a lower level.

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