A Framework for Energy-Efficient Clustering With Utilizing Wireless Energy Balancer

• Main Authors: Aliaa M. Alabdali, Niayesh Gharaei, Arwa A. Mashat
• Format: Article
• Language: English
• Published: IEEE 2021-01-01
• Series: IEEE Access
• Subjects: Wireless sensor network; clustering; energy balancer; energy efficiency
• Online Access: https://ieeexplore.ieee.org/document/9521531/

Clustering has been accepted as one of the most efficient techniques for conserving the energy of wireless sensor networks (WSNs). In cluster-based WSN, the cluster heads (CH) consume more energy compared with normal nodes, which results in rising their energy consumption and reducing the network lifetime. There are several energy-efficient routing schemes which have been presented to reduce the energy consumption of CHs. In such schemes, further clustering of CHs will result in reducing the energy consumption of CHs. However, this rule has not been considered in previous related works. Likewise, unbalanced energy consumption of CHs is one the main design challenges which leads to increase the wasted energy and premature network death. A number of recent studies have sought to improve the balanced energy via utilizing devices equipped with large and expensive energy harvesters, which leads to extra cost Therefore, a feasible solution is needed to achieve balanced energy consumption of CHs. Consequently, to overcome the aforementioned limitations, we proposed a framework for energy-efficient clustering by utilizing a wireless energy balancer. Firstly, an n-level clustering is presented which results in fully leveraging and reducing the energy consumption of CHs. Secondly, an energy balancer is utilized in order to reduce the wasted energy to the fullest possible extent by zeroing the variance between the remaining energy of CHs. The performance of the proposed scheme has been compared against CMS2TO and DGOB mechanisms. Simulation results show that the proposed scheme achieved improved performance in terms of network lifetime by 20%, total energy consumption by 52%, network overhead by 20%, computation time by 46%, and wasted energy by 86% compared to existing schemes. In conclusion, the proposed framework proves to be a viable solution for enhancing the network lifetime and energy efficiency.