A Novel Control Plane Optimization Strategy for Important Nodes in SDN-IoT Networks

One of the crucial technologies for future Internet of Things (IoT) is software defined networks, which provides a centralized and programmable control ability for operators. However, the current single control plane deployed on the remote IoT gateway may incur a bottleneck with the continuous growth of IoT devices and applications. In this paper, we propose a two-level hierarchy (the master and slave) control framework to resolve this problem. Additionally, a novel slave controller placement strategy (SCPS) is presented to further optimize the control performance. In SCPS, we first design a synthetic IoT node importance assessment model based on an improved analytic hierarchy process and fuzzy integral. It considers the device attributes, service attributes, and control frequency. Then we formulate the slave controller placement as a binary integer program problem. It is solved by a modified binary particle swarm optimization algorithm to optimize the control delay and control cost of critical IoT nodes. Finally, we carry out extensive experiments to evaluate the performance of our strategy. The results show that, compared to other competing methods, it approximately reduces the control delay of important IoT nodes by 30.56%.