A relaxed and faster switch migration framework to balance the load of distributed control plane in software defined networks.

By decoupling the data plane and the control plane of networking devices, Software Defined Network (SDN) enables the control plane devices to obtain the abstract view of the entire network and accomplish network functions as necessary. In SDN, control plane device, known as SDN controller is responsible for managing and setting rules for the data plane devices (SDN switches). Multiple SDN controllers are often used to formulate distributed controller architecture for geographically larger networks where different sets of switches are connected to and managed by different controllers. Due to network dynamics, any particular controller can become overloaded which results in increased response time and thereby reduce the end-user quality of service. To tackle the controller overload issue, in this paper, an effective and efficient load balancing framework is proposed. Most of the previous works in this domain focus on precise load balancing; therefore many load shifting (switch migration) operations are required and consequently degrade the end-user QoS. Additionally, beneath a certain load, CPU performs almost equally well; therefore load balancing before reaching a certain controller's load seems unnecessary and questionable. Unlike most of the previous works, our algorithm balances the load loosely in a proper distributed controller SDN architecture. The load balancing framework uses five key modules to perform faster switch migrations to balance the load. Number of switch migrations, selection time performance, and load balancing precision are the performance metrics for evaluation and comparison for this work. The resultant load-balancing solution has successfully shown its potency in terms of reducing the number of switch migrations and the selection time compared to some recent and notable works in this domain. Moreover, a completely new functionality named Switch Restoration is introduced in our load balancing solution to optimize the network further. [ABSTRACT FROM AUTHOR]