Enhanced Dual-Selection Krill Herd Strategy for Optimizing Network Lifetime and Stability in Wireless Sensor...

Area of Science:

• Computer Science
• Network Engineering
• Optimization Algorithms

Background:

• Wireless sensor networks (WSNs) face critical energy management challenges.
• Maximizing network lifetime, coverage, and data aggregation are key operational goals.
• Efficient energy conservation is vital for sensor node deployment and scalability.

Purpose of the Study:

• To introduce an enhanced dual-selection krill herd (KH) optimization clustering scheme for resource-efficient WSNs.
• To address energy conservation challenges in WSNs through optimized node deployment and clustering.
• To improve overall energy utilization and reduce inter-node communication.

Main Methods:

• Developed an enhanced dual-selection krill herd (KH) optimization clustering scheme.
• Implemented a dynamic layering mechanism to prevent repetitive cluster head selection.
• Utilized a modified krill-based clustering method for enhanced exploitation and exploration.

Main Results:

• Achieved a 23.21% enhancement in network lifetime.
• Increased stable energy by 19.84%.
• Reduced network latency by 22.88% compared to benchmark approaches.

Conclusions:

• The proposed KH optimization clustering scheme offers a more efficient and reliable solution for WSN energy management.
• The dynamic layering and dual-selection mechanisms contribute to improved network performance.
• This approach effectively addresses critical challenges in WSN operational efficiency and longevity.