Residual-Energy LEACH-PSO Extends Simulated WSN Lifetime under Uneven Node Density

Authors

  • Ramdan Satra Universitas Muslim Indonesia
  • Muhammad Hattah Fattah Universitas Muslim Indonesia

DOI:

https://doi.org/10.56705/ijodas.v7i2.529

Keywords:

Wireless Sensor Networks, LEACH-PSO, Residual-energy Cluster-head Selection, Network Lifetime, Topology-paired Simulation

Abstract

Introduction: Uneven spatial node density can concentrate communication burdens in wireless sensor networks (WSNs). This study evaluated the incremental effect of residual-energy cluster-head reassignment on simulated network lifetime. Method: LEACH (M1), particle swarm optimization (PSO) seed clustering (M2), and residual-energy LEACH-PSO (M3) were evaluated across 270 synthetic topologies covering nine near–far scenarios with 30 placements each, producing 810 method runs. Every topology contained 200 nodes in a fixed 200 m × 200 m field. M2 and M3 shared radio, traffic, and PSO settings. Within each logical round, M3 retained the PSO-derived membership and selected the member with the highest residual energy after status transmission as cluster head. The primary topology-paired M3–M2 comparison assessed first-node-dead (FND) and half-nodes-dead (HND) rounds using block-bootstrap confidence intervals. Results and Discussion: Mean FND and HND were 18.70 and 39.85 rounds for M3, compared with 8.84 and 32.84 for M2. Aggregate paired gains were 9.86 FND rounds (95% CI, 9.44–10.26) and 7.01 HND rounds (95% CI, 6.83–7.19). Both endpoints improved on average in all nine scenarios, with the largest gains when 180 nodes occupied the far zone. No endpoints were censored. Conclusion: Cluster-head reassignment based on residual energy extended simulated WSN lifetime under the specified radio and traffic model. Performance under realistic communication conditions and physical deployments requires further validation.

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Published

2026-07-31

How to Cite

Residual-Energy LEACH-PSO Extends Simulated WSN Lifetime under Uneven Node Density. (2026). Indonesian Journal of Data and Science, 7(2), 434-443. https://doi.org/10.56705/ijodas.v7i2.529