Charger placement optimization in wireless sensor networks using hybrid graph coloring and Enhanced Aquila Optimization
P Neelagandan, S Balaji · 2026
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Description
P Neelagandan's team optimized charger placement in 2026 for wireless sensor networks, where dead sensors break coverage and sustainability hinges on smart charging. A two-stage framework first counts the fewest chargers needed using hybrid graph coloring, then places them with an eagle-inspired Enhanced Aquila Optimization under coverage and power limits. Tests compared the method against several rival optimizers.
Enhanced Aquila reached ninety-nine percent coverage with faster convergence. It beat raindrop, grey wolf, black hole, dragonfly, and standard Aquila methods by clear margins, while the upgrade added six percent coverage over the base algorithm. Network engineers get a scalable, energy-aware deployment recipe. Real terrain and obstacle tests remain to confirm lab gains.
Catalog record
| CREATOR | P Neelagandan, S Balaji |
|---|---|
| YEAR | 2026 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 62 KB |
| VERSION | 1.0 |
| LICENSE | CC BY 4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |