Open Access

ARTICLE

LOA-RPL: Novel Energy-Efficient Routing Protocol for the Internet of Things Using Lion Optimization Algorithm to Maximize Network Lifetime

Sankar Sennan¹, Somula Ramasubbareddy², Anand Nayyar^3,4, Yunyoung Nam^5,*, Mohamed Abouhawwash^6,7

1 Department of Computer Science Engineering, Sona College of Technology, Salem, 636005, India
2 VNR Vignana Jyothi Institute of Engineering & Technology, Hyderabad, 500090, India
3 Graduate School, Duy Tan University, Da Nang, Vietnam, 550000, Vietnam
4 Faculty of Information Technology, Duy Tan University, Da Nang, Vietnam, 550000, Vietnam
5 Department of Computer Science and Engineering, Soonchunhyang University, Asan, 31538, Korea
6 Department of Mathematics, Faculty of Science, Mansoura University, Mansoura, 35516, Egypt
7 Department of Electrical and Computer Engineering, Michigan State University, East Lansing, MI, 48824, USA

* Corresponding Author: Yunyoung Nam. Email:

(This article belongs to the Special Issue: Emerging Trends in Artificial Intelligence and Machine Learning)

Computers, Materials & Continua 2021, 69(1), 351-371. https://doi.org/10.32604/cmc.2021.017360

Received 28 January 2021; Accepted 13 March 2021; Issue published 04 June 2021

Abstract

Energy conservation is a significant task in the Internet of Things (IoT) because IoT involves highly resource-constrained devices. Clustering is an effective technique for saving energy by reducing duplicate data. In a clustering protocol, the selection of a cluster head (CH) plays a key role in prolonging the lifetime of a network. However, most cluster-based protocols, including routing protocols for low-power and lossy networks (RPLs), have used fuzzy logic and probabilistic approaches to select the CH node. Consequently, early battery depletion is produced near the sink. To overcome this issue, a lion optimization algorithm (LOA) for selecting CH in RPL is proposed in this study. LOA-RPL comprises three processes: cluster formation, CH selection, and route establishment. A cluster is formed using the Euclidean distance. CH selection is performed using LOA. Route establishment is implemented using residual energy information. An extensive simulation is conducted in the network simulator ns-3 on various parameters, such as network lifetime, power consumption, packet delivery ratio (PDR), and throughput. The performance of LOA-RPL is also compared with those of RPL, fuzzy rule-based energy-efficient clustering and immune-inspired routing (FEEC-IIR), and the routing scheme for IoT that uses shuffled frog-leaping optimization algorithm (RISA-RPL). The performance evaluation metrics used in this study are network lifetime, power consumption, PDR, and throughput. The proposed LOA-RPL increases network lifetime by 20% and PDR by 5%–10% compared with RPL, FEEC-IIR, and RISA-RPL. LOA-RPL is also highly energy-efficient compared with other similar routing protocols.

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Keywords

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