Software-defined networking (SDN) is proposed as a new network paradigm which decouples control plane from data plane and provides flexible network management. In this paper, we consider the capacitated controller placement problem in SDN, which jointly determines the number, location, and the capacity matching strategy of SDN controllers. redTo stress the importance of control plane delay which is composed of both the transmission and processing delay between controllers and switches, and the inter-controller delay; we formulate control plane delay minimization problem subject to controller-switch association constraints, controller capacity constraints, etc. Since the formulated optimization problem is a complicated nonlinear integer programming problem which cannot be solved easily, we transform it into controller-switch association subproblem and controller capacity matching subproblem. To solve the controller-switch association subproblem, we propose a heuristic algorithm based on Dijkstra algorithm and K-means algorithm. Given the controller-switch association strategy, we then apply the Kuhn-Munkres (K-M) algorithm to solve the controller capacity matching subproblem and obtain the capacitated controller placement strategy. Simulation results are shown to demonstrate the effectiveness of the proposed algorithm.
Software-defined networking (SDN) technology is expected to offer higher flexibility and programmability and enhanced transmission performance by decoupling control plane from data plane and enabling centralized network management. In SDN, switches may cache a certain number of flow forwarding rules, so that user flows can be forwarded accordingly. In this article, stressing the limited caching space of switches and the heterogeneous transmission performance of switches and links, we jointly design rule caching and flow forwarding strategy for multiple user flows in SDN. To emphasize the importance of the end-to-end delay caused by the transmission and processing of user flows in both the data plane and control plane, we formulate the joint optimization problem as an end-to-end delay minimization problem. As the original optimization problem is a non-deterministic polynomial hard (NP-hard) problem, which cannot be solved directly, we propose a heuristic algorithm which successively solves three subproblems, i.e., flow forwarding subproblem, rule caching and candidate path selection subproblem, and resource sharing subproblem. By applying the K-shortest path algorithm, a priority-based rule caching algorithm, and Lagrangian dual method, respectively, the three subproblems are solved and the joint rule caching and flow forwarding strategy is obtained. Simulation experiments are conducted to examine the effectiveness of the proposed algorithm, and the results indicate that our proposed algorithm is capable of improving system performance by about 20% compared with the previous solutions.INDEX TERMS Software-defined networking, end-to-end delay, rule caching, flow forwarding, resource sharing.
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