Modified power line system-based energy efficient routing protocol to improve network life time in 5G networks. (March 2023)

• Record Type: Journal Article
• Authors: Alqahtani, Hamed; Niranjan, L; Parthasarathy, P; Mubarakali, Azath
• Is Part Of: Computers & electrical engineering. Volume 106(2023)
• Publication Date: 2023-03
• Subjects: Energy balance -- Wireless sensor network -- Cluster head -- Optimal outing -- Cluster head low energy adaptive clustering hierarchy -- Low-energy adaptive clustering hierarchy; Computer engineering -- Periodicals; Electrical engineering -- Periodicals; Electrical engineering -- Data processing -- Periodicals; Ordinateurs -- Conception et construction -- Périodiques; Électrotechnique -- Périodiques; Électrotechnique -- Informatique -- Périodiques; Computer engineering; Electrical engineering; Electrical engineering -- Data processing; Periodicals; Electronic journals; 621.302854
• DOI: 10.1016/j.compeleceng.2022.108564
• Languages: English
• ISSNs: 0045-7906

Abstract

Abstract: One of the main issues with wireless sensor networks (WSNs) is that most of the sensor nodes are powered by batteries with a finite lifespan, which has a significant impact on the performance, quality, and lifespan of the network. Over the past decade, energy-efficient routing methods were utilized to improve the network lifetime. In this work, we implemented a novel routing protocol-based modified power line system to improve the network lifetime in 5G networks. The technique of data transfer with the optimum hop count is presented based on energy balancing, which completely minimizes the energy usage of data transmission. In some specific applications, the nodes must work at a similar time, and the effective working time of systems is determined by identifying the node with the highest energy levels in the network. The proposed M-POLC shows the highest energy level as compared to LEACH, EEUC, and CH LEACH for 200 nodes with 50 iterations. The Modified Power Line System (M-POLC) has more alive nodes compared to Energy-Efficient Uneven Clustering (EEUC) which has 70% alive nodes, Low-Energy Adaptive Clustering Hierarchy (LEACH) with 50% alive nodes, and Cluster Head Low Energy Adaptive Clustering Hierarchy (CH LEACH) with less than 20% alive nodes. Simulation outcomes suggest that the proposed strategy significantly reduces energy usage while also extending the lifetime of WSNs in 5G networks.