Congestion Aware Algorithm using Fuzzy Logic to Find an Optimal Routing Path for IoT Networks

• Published in: 2019 International Conference on Computational Intelligence and Knowledge Economy (ICCIKE) pp. 141 - 145
• Main Authors: J, Shreyas, Singh, Hemant, Bhutani, Jatin, Pandit, Sanjay, N, Srinidhi N, Kumar S M, Dilip
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01-12-2019
• Subjects: Biological system modeling; Congestion Aware Algorithm using Fuzzy Logic (CAUF); Decision making; Fuzzy logic; Fuzzy Logic (FL); Internet of Things (IoT); Linear programming; Measurement; Multi Attribute Decision Making (MADM); Routing; Routing protocols
• DOI: 10.1109/ICCIKE47802.2019.9004351

Internet of Things (IoT) is a rapidly expanding technology that has recently got significant recognition in the field of studies. In IoT networks, huge traffic in network causes congestion at nodes that influences the quality of routing metrics the overall performance of the network. Therefore in this paper, congestion aware algorithm using fuzzy logic (CAUF) has been proposed to avoid congestion by selecting the best parent in a tree structured IoT network to find the optimal routing path. It models the problem of parent selection into multi attribute decision making (MADM) based problem using fuzzy weighted sum model. CAUF has been implemented and simulated on cooja simulator and a comparison of performance is carried out with queue utilization based RPL (QU-RPL) and optimization based hybrid congestion alleviation (OHCA) algorithms. Simulation results indicate that proposed has 15% more throughput and 4.5% packets less dropped over OHCA and QU-RPL algorithms.