Distributed dynamic scheduling algorithm of target coverage for wireless sensor networks with hybrid energy...

Area of Science:

• Computer Science
• Electrical Engineering
• Network Engineering

Background:

• Wireless sensor networks (WSNs) face challenges in prolonged target monitoring due to the unpredictable nature of hybrid energy harvesting (solar and wind).
• Optimizing energy utilization for effective target coverage in WSNs with stochastic energy arrivals is a critical research problem.

Purpose of the Study:

• To develop a dynamic and distributed node scheduling algorithm for hybrid energy-harvesting WSNs (HEH-WSNs).
• To maximize long-term average coverage utility under peak power constraints using Lyapunov optimization.
• To address the challenge of optimizing energy utilization for target coverage in WSNs with fluctuating energy sources.

Main Methods:

• Formulation of maximum long-term average coverage utility subject to peak power constraints.
• Application of Lyapunov optimization theory to create a dynamic potential game framework for target coverage.
• Derivation of a distributed dynamic target-coverage node scheduling algorithm (DTNSA) from the potential game.

Main Results:

• The proposed DTNSA significantly enhances average coverage utility compared to existing algorithms in simulations.
• DTNSA demonstrates a reduction in the average number of active sensor nodes and average coverage redundancy.
• The algorithm shows effective adaptation to dynamic changes in harvested energy and lower computational complexity.

Conclusions:

• The developed distributed dynamic target-coverage node scheduling algorithm (DTNSA) offers a robust solution for HEH-WSNs.
• DTNSA provides superior performance in terms of coverage utility and resource management.
• The algorithm's adaptability and efficiency make it a promising approach for sustainable WSN operations.