Energy-Optimized Routing in WSNs: Enhanced Dijkstra-Based MEP and EBP Approaches

Authors

  • Hala Nazmy Information Systems Department, Faculty of Computers and Informatics, Suez Canal University, Ismailia, Egypt
  • BenBella Sayed Tawfik Information Systems Department, Faculty of Computers and Informatics, Suez Canal University, Ismailia, Egypt
  • Mohamed Abdallah Makhlouf Information Systems Department, Faculty of Computers and Informatics, Suez Canal University, Ismailia, Egypt
  • Osama Farouk Information Systems Department, Faculty of Computers and Informatics, Suez Canal University, Ismailia, Egypt

DOI:

https://doi.org/10.19139/soic-2310-5070-2573

Keywords:

Wireless Sensor Networks (WSNs), Energy Efficiency, Dijkstra’s Algorithm, Load Balancing, Network Lifetime, Routing Optimization.

Abstract

Wireless Sensor Networks (WSNs) require energy-efficient routing to extend network lifetime due to limited node battery capacity. This paper presents two improved Dijkstra-based algorithms—Minimum Energy Path (MEP) Dijkstra, which minimizes per-packet energy consumption, and Energy-Balanced Path (EBP) Dijkstra, which dynamically adjusts paths to distribute energy usage evenly—enhancing both efficiency and fairness. Through extensive simulations, we show that EBP increases network lifetime by 97.3% compared to MEP while maintaining balanced energy consumption. Our contributions include complete algorithm pseudocode with complexity analysis, an accurate energy consumption model for realistic WSN scenarios, a comparative study with 12 state-of-the-art methods, and sensitivity analysis on key parameters such as balancing factor (β), network density, and traffic patterns. The results demonstrate significant improvements in energy efficiency, providing practical insights for WSN deployment in IoT and remote monitoring applications.    

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Published

2025-06-23

Issue

Vol. 14 No. 3 (2025)

Section

Research Articles

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How to Cite

Energy-Optimized Routing in WSNs: Enhanced Dijkstra-Based MEP and EBP Approaches. (2025). Statistics, Optimization & Information Computing, 14(3), 1252-1269. https://doi.org/10.19139/soic-2310-5070-2573