Load and congestion aware routing protocol for heterogeneous traffic loaded IoT networks
Arya Paul, Anju S. Pillai, Krishna Priya R · Engineering Research Express · 2025
Abstract The Internet of Things (IoT) has gained much attention recently because of its prominent role in setting up smart products and technologies that utilize their intelligence. A Wireless Sensor Network (WSN), a vital part of an IoT system, comprises numerous tiny sensors that sense an object’s physical properties and transmit information hop by hop to a central device (sink node) through low-power and short-range transceivers. In many IoT applications, sensor nodes generate multiple data streams with varying demands for data generation or transmission rates, reliability and delay, resulting in a heterogeneous or diverse traffic load. Even though the Routing Protocol for Low Power and Lossy Networks (RPL), an IPv6 standard, is intended to meet the Quality of Service (QoS) needs of low-power IoT deployments, it exhibits poor load balancing in networks with diverse traffic loads. This research proposes Load and Congestion Aware RPL (LCARPL) that concentrates on enhancing the energy efficiency and reliability of these heterogeneous traffic loaded networks with nodes having different data generation or transmission rates, by utilizing load and packet delay metrics for determining the best parent node. Grey Relational Analysis (GRA) is used to select the best parent from potential candidates. The Cooja simulation results demonstrate a significant improvement in the performance of a heterogeneous traffic loaded network across packet delivery, energy usage, delay and control message overheads. Moreover, the work provides a comprehensive assessment of the RPL network using two standard objective functions by evaluating and comparing its performance under both homogeneous and heterogeneous conditions across varying numbers of IoT nodes.