Pushing IoT Mobility Management to the Edge: Granting RPL Accurate Localization and Routing

Accurate and timely mobility support in Internet of Things (IoT) applications is a challenging issue, considering the inherent scarce resources of IoT devices. However, the computational, memory and communication burden may be pushed into more ”muscled” Software Defined Network (SDN) controllers. A centralised controller can exploit its global view of the network and predict the handovers and update the routing tables just in time to keep the mobile nodes connected. However, it requires the mobility solution to be enhanced with extra link quality information to estimate the distance between mobile and static nodes while avoiding collision between the new control overhead for localization and other communications in the network. In this work we present SDMob, an SDN-based mobility management architecture that lifts the burden of computation intensive filtering algorithms from resource constrained nodes and achieves accurate and fast handovers upon nodes’ mobility under Routing Protocol for Lossy Low-power Networks (RPL) and IPv6 over Low-Power Wireless Personal Area Networks (6LoWPAN). We show that SDMob improves the baseline RPL and the state-of-the-art mRPL in terms of packet delivery ratio leveraging more reliable routing and applying Particle filter and variations of Kalman filter on radio signal strength data enables more accurate localization for complex real world trajectories.