Neuro-Fuzzy-Based Routing Mechanism for Effective Communication in 6LoWPAN-Based IoT Infrastructure

Abstract

IoT (Internet of Things) devices that are IEEE 802.15.4 compliant are used to build 6LoWPANs (IPv6-based Low Power Personal Area Networks). For most IoT applications' network systems, 6LoWPA is the wireless technology of choice. However, the various IoT systems produce diverse routing patterns in actual network implementation. An objective of such a strategy is to enhance connectivity while ensuring route stability throughout the network at all times.Neuro-Fuzzy Based Routing Mechanism for efficient routing in 6LoWPAN-based IoT infrastructure is proposed. Using neural networks, fuzzy systems can incorporate the computational properties of training the input data into their representations and gain the coherence and interpretation they need. This research finding shows that the suggested routing strategy provides improved communication effectiveness in regards to packet transmission (93%) and other parameters such as energy usage (2.33%) and latency (7.42%).