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A Traffic-Aware and Cluster-Based Energy Efficient Routing Protocol for IoT-Assisted WSNs
1 Department of Computer and Software Technology, University of Swat, Mingora, 19130, Pakistan
2 Department of Computer Science and Engineering, Chungnam National University, Daejeon, 34134, Republic of Korea
3 Department of Applied AI, Sungkyunkwan University, Seoul, 03063, Republic of Korea
* Corresponding Author: Ki-Il Kim. Email:
(This article belongs to the Special Issue: Distributed Computing with Applications to IoT and BlockChain)
Computers, Materials & Continua 2024, 80(2), 1831-1850. https://doi.org/10.32604/cmc.2024.052841
Received 17 April 2024; Accepted 05 July 2024; Issue published 15 August 2024
Abstract
The seamless integration of intelligent Internet of Things devices with conventional wireless sensor networks has revolutionized data communication for different applications, such as remote health monitoring, industrial monitoring, transportation, and smart agriculture. Efficient and reliable data routing is one of the major challenges in the Internet of Things network due to the heterogeneity of nodes. This paper presents a traffic-aware, cluster-based, and energy-efficient routing protocol that employs traffic-aware and cluster-based techniques to improve the data delivery in such networks. The proposed protocol divides the network into clusters where optimal cluster heads are selected among super and normal nodes based on their residual energies. The protocol considers multi-criteria attributes, i.e., energy, traffic load, and distance parameters to select the next hop for data delivery towards the base station. The performance of the proposed protocol is evaluated through the network simulator NS3.40. For different traffic rates, number of nodes, and different packet sizes, the proposed protocol outperformed LoRaWAN in terms of end-to-end packet delivery ratio, energy consumption, end-to-end delay, and network lifetime. For 100 nodes, the proposed protocol achieved a 13% improvement in packet delivery ratio, 10 ms improvement in delay, and 10 mJ improvement in average energy consumption over LoRaWAN.Keywords
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