Energy-Efficient Clustering and Routing Using ASFO and a Cross-Layer-Based Expedient Routing Protocol for Wireless...

Area of Science:

• Computer Science
• Electrical Engineering
• Network Engineering

Background:

• Wireless Sensor Networks (WSNs) face critical challenges in extending operational lifetime and reducing power consumption.
• Energy limitations in WSNs include clustering, storage, communication capacity, complexity, speed, and computation, with cluster head selection being a key issue for energy minimization.
• Optimal energy resource utilization is essential due to these constraints.

Purpose of the Study:

• To optimize cluster head selection in WSNs for improved energy efficiency.
• To minimize energy consumption, reduce node distance, and decrease latency through intelligent clustering.
• To enhance overall network performance and longevity.

Main Methods:

• Utilized the Adaptive Sailfish Optimization (ASFO) algorithm combined with K-medoids for sensor node clustering.
• Implemented an energy-efficient cross-layer-based expedient routing protocol (E-CERP) for dynamic shortest route determination and network overhead minimization.
• Evaluated performance based on packet delivery ratio (PDR), packet delay, throughput, power consumption, network lifetime, packet loss rate (PLR), and error estimation.

Main Results:

• Achieved a 100% Packet Delivery Ratio (PDR).
• Demonstrated minimal packet delay (0.05 s) and packet loss rate (0.5%) for 100 nodes.
• Reported high throughput (0.99 Mbps), low power consumption (1.97 mJ), and an extended network lifespan (5908 rounds).

Conclusions:

• The proposed ASFO with K-medoids clustering and E-CERP routing significantly outperforms existing methods in WSNs.
• The approach effectively addresses energy limitations, optimizes cluster head selection, and enhances quality-of-service parameters.
• This research contributes to more sustainable and efficient wireless sensor network operations.