Home > Published Issues > 2023 > Volume 18, No. 6, June 2023 >
JCM 2023 Vol.18(6): 346-356
Doi: 10.12720/jcm.18.6.346-356

Mobility Assisted Adaptive Clustering Hierarchy for IoT Based Sensor Networks in 5G and Beyond

Biswanath Dey1,*, Sivaji Bandyopadhyay1, and Sukumar Nandi2
1.National Institute of Technology Silchar, Silchar 788010, India
2.Indian Institute of Technology Guwahati, North Guwahati 781039, India
*Correspondence: bdey33@yahoo.com (B.D.)

Manuscript received July 13, 2022; revised September 23, 2022; accepted November 23, 2022.

Abstract—One of the massive machine type communication (mMTC) applications for monitoring and sensing in 5G cellular network is the Internet of Things (IoT) based wireless sensor network (WSN). Non uniform battery usage by the nodes in these networks often results in creating energy holes or voids in the network making the network disconnected. An effective solution is to deploy multiple mobile nodes throughout the network, however finding optimal path for these mobile nodes is reported to be an NP hard problem. This paper proposes MAACH (Mobility Assisted Adaptive Clustering Hierarchy), an efficient mobility assisted clustering and routing framework for IoT based sensor network in 5G and beyond. Also, an elaborate method to calculate the exact path optimally for multiple mobile nodes is presented to alleviate non uniform energy dissipation of the sensing nodes. Simulation results show that our algorithm effectively finds the optimal trajectory of multiple mobile nodes in a distribute manner and also improves network stability period by 60-70% and the network lifetime by 70-90% across multiple network deployments.

Keywords—IoT based sensor network, mobile nodes, clustering, routing, energy efficiency, network lifetime, 5G and beyond

Cite: Biswanath Dey, Sivaji Bandyopadhyay, and Sukumar Nandi, "Mobility Assisted Adaptive Clustering Hierarchy for IoT Based Sensor Networks in 5G and Beyond," Journal of Communications, vol. 18, no. 6, pp. 346-356, June 2023. 

Copyright © 2023 by the authors. This is an open access article distributed under the Creative Commons Attribution License (CC BY-NC-ND 4.0), which permits use, distribution and reproduction in any medium, provided that the article is properly cited, the use is non-commercial and no modifications or adaptations are made.