Fuzzy optimised routing metric with mobility support for RPL

Abstract

Recently, many Internet of Things (IoT) applications have emerged with mobility as a fundamental requirement. The presence of a mobile node that changes location around the application domain affects the performance of the Routing Protocol for Low Power Lossy Network (RPL) designed for IoT, leading to repeated disruptions that cause data loss and more power dissipation. In this study, a fuzzy optimised routing metric with mobility support (FL-RPL) has been proposed to enhance the performance of the RPL. The fuzzy inference system considers various routing metrics to pick a suitable candidate parent as the preferred parent node to forward the data to the sink node. Further, timer functions have been added to maintain consistent neighbours to support mobility and seamless connectivity. The FL-RPL has been implemented and tested with different parameter settings for a practical scenario. The obtained simulation results clearly demonstrated that the proposed solution increased packet delivery ratio by approximately 12%, and reduced power consumption by 20% compared with the standard RPL. 2019 The Institution of Engineering and Technology.