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This research aims to optimize energy efficiency and reduce delays in wireless sensor networks through effective clustering and routing techniques.

July 10, 2026Scientific ReportsOpen Access

Multi-objective optimization approach for energy efficient clustering and routing in wireless sensor networks

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This research aims to optimize energy efficiency and reduce delays in wireless sensor networks through effective clustering and routing techniques.
Proposed Multi-Objective Di-Strategy GrayLag Goose Optimization (MO-DSGGO) for energy-efficient routing.
Utilized fitness functions based on intra-cluster distance, cluster head to base station distance, and residual energy.
Scenarios tested with varying node counts, achieving metrics evaluated in MATLAB R2020b.
Achieved a delay of 0.176 ms and energy consumption of 7.2 J for 100 nodes in scenario 2.
Obtained a throughput of 95% for 250 nodes in scenario 7.
Achieved a longer node lifetime of 97.272% with a Packet Delivery Ratio (PDR) of 95.38% compared to existing methods.

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Randomized trial reveals improved energy efficiency and reduced delay in wireless sensor networks, indicating better network performance.

Madhankumar et al. (2026) studied this question.

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