Controller Placement Problem Optimization in Software Defined Networks Using Intelligent Methods
Keywords:
Controller - Software Defined Networks – Problem OptimizationAbstract
Software-Defined Networks are new paradigm of networks that separate control plane from data plane, hence transforming the network into a logically centralized network. In this type of networks, the control plane is assumed to have a global view of the network, therefore providing a more efficient management of the network. Control plane performs the management by means of “Controllers”, which are the master-mind of the network. Controllers can operate along with a number of other controllers, while all being logically centralized. Choosing proper number of controllers and the best locations for them, are among the important challenges of SDN which influence network "performance". An additional important challenge of SDN networks is scalability. In this paper we introduce a linear optimization model with the following goals: increasing scalability, reducing delay, reducing cost, reducing the number of control messages, and providing load balancing in the network. We solved the model and analyzed the problem. The proposed model assumes the network links to be in-band in order to provide scalability and to reduce costs. It means not all of the switches will directly connect to the controllers; instead, some of the switch-to-controller connections will be indirect – through other switches. The assumption of intermediate switches, and also the severally number of objectives in optimization will furtherly complicate the model, causing the model to become non-linear. In this paper, we propose a linear model that has a global unique solution in small scale. Then we suggest two algorithms for solving this model in shorter time: Using Genetic algorithm and Tabu Search. Next, we compare cost and run time for the two suggested algorithms, and also compare the results of the algorithms with each other.
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