Mobility-Aware Flow-Table Implementation in Software-Defined IoT

In this paper, we propose a mobility-aware flow-table implementation scheme with an aim to maximize overall network performance in software-defined IoT. The proposed scheme consists of two components - path estimator and flow-manager. The path estimator predicts future locations of end devices present in the network, and delivers info to the flow-manager. Based on predicted locations, the flow-manager implements forwarding rules at access devices (ADs) in the network, so that adequate actions for incoming requests can be taken immediately without asking the controller. We use order-k Markov predictor to predict the next possible locations of the end devices. We consider a practical scenario of an IoT environment, in which both static and mobile devices are present. Extensive simulation results show that the proposed scheme is beneficial for improving network performance in terms of energy consumption and message overhead for flow-table implementation, while predicting the future locations of the devices. We show that the proposed scheme is capable of enhancing the overall network performance approximately by 50%.