Pre-Scheduled and Self Organized Sleep-Scheduling Algorithms for Efficient K-Coverage in Wireless Sensor Networks.

Area of Science:

• Computer Science
• Electrical Engineering
• Network Engineering

Background:

• K-coverage is crucial for wireless sensor networks (WSNs) ensuring reliable monitoring.
• Existing sleep-scheduling algorithms for K-coverage face challenges with high costs or compromised detection quality.
• Optimizing network lifetime and detection quality are key objectives for K-covered WSNs.

Purpose of the Study:

• To address limitations in existing K-coverage sleep-scheduling algorithms.
• To introduce novel algorithms, Pre-Scheduling-based K-coverage Group Scheduling (PSKGS) and Self-Organized K-coverage Scheduling (SKS).
• To enhance network lifetime and detection quality in WSNs.

Main Methods:

• Development of the Pre-Scheduling-based K-coverage Group Scheduling (PSKGS) algorithm.
• Development of the Self-Organized K-coverage Scheduling (SKS) algorithm.
• Simulation-based evaluation of PSKGS and SKS performance.

Main Results:

• PSKGS enhances detection quality and network lifetime compared to existing methods.
• SKS minimizes computation and communication costs, leading to energy efficiency.
• SKS demonstrates superior performance over PSKGS in network lifetime and detection quality due to its self-organized nature.

Conclusions:

• PSKGS and SKS offer effective solutions for K-coverage sleep scheduling in WSNs.
• SKS provides a more energy-efficient and robust approach for achieving K-coverage.
• The proposed algorithms contribute to improved WSN performance for monitoring applications.