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Energy-Efficient Coverage Optimization in WSN Using the Krill Herd Optimization Algorithm
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AI
DOI：10.1080/03772063.2026.2623055.png)
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Abstract
En 中文
Wireless Sensor Networks (WSNs) have faced significant challenges regarding maximizing the coverage area with a focus on energy-saving and network longevity. Most previous approaches have only considered several optimization goals, without taking into account relationships between energy, coverage, and power equality. To address these gaps, this paper proposes an Energy Efficient Coverage Optimization in WSN using Krill Herd Optimization Algorithm (EECO-WSN-KHOA). The proposed method simultaneously includes three objectives, such as reducing energy consumption, increasing coverage rate, and enhancing the balance of energy consumption across the network. Here, the Krill Herd Optimization Algorithm (KHOA) is proposed to efficiently optimize the sub-problems present in this multi-objective issue in WSN by ensuring a balanced trade-off between network lifetime and coverage rate. Key parameters considered include network size (100 & times; 100 m), number of sensor nodes (200), sensing range (20 m), transmission range (50 m), initial energy (1-2 J), data packet size (100-1024 bytes), and simulation duration (5000 s). The proposed approach is implemented in NS2 software and evaluated using performance metrics like computation time (CT), residual energy (RE) and energy consumption (EC) for different sensor nodes. The proposed method provides 32.24%, 22.09%, and 27.21% higher residual energy; 22.56%, 21.31%, and 23.52% higher coverage rate than the existing models. The outcomes show that the proposed method addresses limitations of existing works by increasing network lifespan and improving coverage through detailed experimental validation.
Keywords:
Coverage rate
energy consumption
Krill herd optimization
residual energy
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