Context-aware Multipath Load Balancing Routing for RPL in IoT

Abstract

The Internet of Things (IoT) is revolutionizing the world with unprecedented levels of insights and intelligence, connecting the physical world to the digital age. In order to provide dependable and efficient routing, IPv6 Routing Protocol for Low Power and Lossy Networks (RPL) has been adopted as the foundation network for the Internet of Things (IoT). Although many IoT routing criteria have been met thanks to RPL's distinctive features, load balancing and congestion control are still the outliers. A context-aware Multipath Load Balancing Routing Protocol (CAMLB-RPL) is proposed that balances the traffic load across multiple paths, minimizing congestion, and increasing network reliability and lifetime. CAMLB-RPL leverages the Context-aware Load Balancing Routing metric (CALBR) to evaluate the queue occupancy and expected lifetime for the chain of parent nodes in the network. A context-aware Load Balancing Objective Function (CALB-OF) is also presented to identify the best-optimized load-balanced route during the parent selection process considering the CALBR and the Child count (CC) metric. A multipath routing strategy is employed to mitigate the congestion due to burst traffic in the network. The performance of CAMLB-RPL was compared to the typical RPL objective functions OF0 and MRHOF using the Cooja simulator of Contiki OS 3.0. CAMLB-RPL showed outstanding results, with power consumption decreasing by 39%, end-to-end delay decreasing by 36%, queue loss ratio declining by 68%, packet receiving rate increasing by 12.5%, and network lifetime increasing by 69%, on average.