Minimizing MultiController Deployment Cost in SoftwareDefined Networking Aiming at various issues, such as performance, loadbalance and robustness, of SoftwareDefined Networking (SDN) controller cluster, several deployment strategies have been proposed. As a supplement, our work delivers a costeffective multicontroller deployment strategy in terms of economic benefits. In this paper, we formalize a Costoptimized MultiController Deployment (COMCD) problem by concerning the controllerxe2x80x99s deployment cost and the network servicexe2x80x99s delay cost. Meanwhile, we characterize the communication between the controller and the switch using a queuing system, and design an algorithm to determine the optimal deployment in the specified environment. Simulation results validate that the proposed algorithm can always obtain a deployment solution which minimizes the economic cost of the entire SDN network. This work aims at being a useful primer to provide insights regarding the economic impact of multiple controllers in the realistic SDN deployment, so that network owners plan their investments more rationally.

Adaptive SDN Master Controller Assignment for Maximizing Network Throughput SoftwareDefined Networking (SDN) controllers are deployed as a cluster in largescale networks, for high availability and scalability. A device (e.g., switch) is connected to multiple controllers in cluster while assigned with one master controller, and the controller with master role is only permitted to manage the device. Therefore, the master controller assignment can affect the network throughput seriously. In this paper, we first study the assignment strategy of two wellknown SDN platforms (i.e., OpenDayLight and Open Network Operating System) as well as the assignment mechanisms in the existing literature, analyzing their deficiencies. Meanwhile, we present an adaptive controller assignment so as to maximize the network throughput under the fluctuating network environment. We formulate this problem as an Integer Linear Program and propose an algorithm based on Ant Colony optimization to solve it efficiently. Extensive experiments validate that our solution is superior to other existing mechanisms in terms of network throughput and load balancing.