4.7 Article

Density cluster based approach for controller placement problem in large-scale software defined networkings

期刊

COMPUTER NETWORKS
卷 112, 期 -, 页码 24-35

出版社

ELSEVIER SCIENCE BV
DOI: 10.1016/j.comnet.2016.10.014

关键词

SDN; Controller placement; Density based clustering; Resilience; Failure tolerance; Latency

资金

  1. China Scholarship Council
  2. National Basic Research Program of China [2013CB329102]
  3. National Natural Science Foundation of China [61671079, 61471063, 61421061, 61372120, 61302087, 61271019]
  4. Beijing Municipal Natural Science Foundation [4152039]
  5. Spanish Research Council [TIN2013-46883]
  6. Regional Government of Madrid - FSE [S2013/ICE-2894]
  7. Regional Government of Madrid - FEDER [S2013/ICE-2894]

向作者/读者索取更多资源

Software Defined Networking (SDN) decouples control and data planes. The separation arises a problem known as the controller placement, i.e., how many and where controllers should be deployed. Currently, most works defined this problem as the multi-objective combinatorial optimization problem and used heuristic algorithms to search the optimal solution. However, these heuristic algorithms have the drawback of being easily trapped in local optimal solutions and consuming high time. In this paper, we propose an approach named as Density Based Controller Placement (DBCP), which uses a density-based switch clustering algorithm to split the network into several sub-networks. As switches are tightly connected within the same sub-network and less connected from the switches in other sub-networks, we deploy one controller in each sub-network. In DBCP, the size of each sub-network can be decided by the capacity of the controller deployed. Moreover, the optimal number of controllers is obtained according to the density-based clustering. We evaluate DBCP's performance on a set of 262 publicly available network topologies. The experimental results show that DBCP provides better performance than the state-of-the-art approaches in terms of time consumption, propagation latency, and fault tolerance. (C) 2016 Elsevier B.V. All rights reserved.

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