Optimal Relay Node Selection for Robust Data Forwarding Over Time-Varying IoT Networks

Abstract

Mobility-tolerant data forwarding over time-varying IoT networks is a challenging problem. Selection of a relay node at every instant in time is crucial and calls for robust and distributed methods to improve the quality of services in such networks. In this paper, an optimal relay node selection method is proposed for robust data forwarding in time-varying networks. The proposed method selects a relay node based on joint optimization of two network parameters, namely data latency and link reliability. The Pareto front of this multi-objective optimization problem is used to illustrate the tradeoff between low data latency and high link reliability. The proposed optimal relay node selection method first identifies all possible relay nodes at every time instant. The weights of the bi-objective problem are updated at every hop and an optimal relay node is selected among all the possible relay nodes, by solving the joint optimization problem. During performance evaluation, random spatial patterns of Internet of Things (IoT) devices are modeled using the homogeneous Poisson point processes. The connectivity duration information of all the IoT devices with their neighbors is updated continuously and a relay node found is in an online manner. Simulation results indicate that the proposed method significantly improves data latency and the packet loss risk for data forwarding over time-varying IoT networks, when compared to conventional single parameter optimization methods. The proposed data forwarding method indicates additional gains in terms of transmission range, mobility tolerance, packet replication cost, and connectivity parameters of the time-varying IoT network.