MDP-Based Model for Interest Scheduling in IoT-NDN Environment

Abstract

Named data networking (NDN) is a novel paradigm that can acknowledge the unprecedented increase in the volume of global IoT traffic which initiates a new network forwarding plane. We propose and evaluate a Markov decision process (MDP)-based scheduler to forward diverse IoT Interests to fitting interfaces in an NDN router to fetch Data with less round trip time (RTT), to meet latency requisites. Simulation results of our MDP model show scheduling Interests to right interfaces reduce the RTT value by 25-30% than existing forwarding strategies. The delay is around 30 ms for higher density of traffic comparatively less than other existing work.