A comparative analysis using LEACH protocol to enhance energy efficiency in wireless sensor networks with harmony search algorithm
Document Type
Article
Publication Title
Discover Computing
Abstract
Wireless sensor networks (WSNs) are critical to many applications, but their use is frequently hampered by energy constraints, particularly in remote locations. WSN nodes are typically installed in remote and frequently inaccessible locations, making battery replacement challenging, thus emphasizing the importance of energy efficiency. This research presents an energy-conserving approach centred on the Harmony Search Algorithm (HSA), optimized by considering key parameters such as the number of sensor nodes, initial energy levels, transmission range, and data rate. The network performance is tested against the LEACH algorithm by evaluating parameters including energy consumption, network lifetime, and throughput. The comparative analysis is performed using graphs depicting the energy consumption of nodes by both approaches. With the Harmony Memory Size (HMS), Harmony Memory Considering Rate (HMCR), and Pitch Adjustment Rate (PAR) adjusted for best outcomes, the suggested method maximizes the performance of WSNs by effectively regulating the energy consumption of sensor nodes. Unlike LEACH, which involves clustering of nodes and periodic rotation of clusters, HSA is based on energy-efficient harmony and does not rely on clustering, thereby finding the most energy-efficient communication path within the network. Simulation results indicate that the HSA algorithm is 9.52% more efficient, with its energy usage being 9.2% more economical compared to the LEACH algorithm. This demonstrates HSA's potential for enhancing WSN performance in energy-constrained environments.
DOI
10.1007/s10791-024-09495-w
Publication Date
12-1-2025
Recommended Citation
Sambhe, Nilesh; Yenurkar, Ganesh; Kanase, Vijay V.; and Anjana, S., "A comparative analysis using LEACH protocol to enhance energy efficiency in wireless sensor networks with harmony search algorithm" (2025). Open Access archive. 11840.
https://impressions.manipal.edu/open-access-archive/11840