An Energy-Efficient Coverage Enhancement Strategy for Wireless Sensor Networks Based on a Dynamic Partition Algorithm...

Area of Science:

• Computer Science
• Electrical Engineering
• Network Engineering

Background:

• Sensor nodes in wireless sensor networks (WSNs) require optimal deployment for effective event coverage.
• Deviations from ideal sensor node placement frequently occur, impacting mission effectiveness and increasing costs.
• Achieving optimal coverage with minimal resource expenditure is a key challenge in WSN design.

Purpose of the Study:

• To determine the optimal deployment locations and minimum number of sensors for maximizing coverage in WSNs.
• To address the multi-objective optimization problem of coverage rate, energy consumption, and energy balancing.
• To develop a robust strategy for sensor node redeployment that enhances coverage and minimizes costs.

Main Methods:

• Splicing sensing areas with cellular grids to identify optimal sensor placement and quantity.
• Transforming the coverage rate and energy consumption optimization into a task assignment problem.
• Proposing a dynamic partition algorithm for cellular grids to handle variable sensor numbers.
• Improving the vampire bat optimizer with virtual bats and preys to solve asymmetric assignment problems.

Main Results:

• The proposed strategy significantly balances residual sensor energy during redeployment compared to three other algorithms.
• Achieved optimization of total sensor node energy cost and coverage rate.
• Demonstrated superior robustness in coverage and energy management when the number of sensor nodes changes.

Conclusions:

• The developed method effectively optimizes sensor node deployment for enhanced coverage and reduced energy costs in WSNs.
• The improved vampire bat optimizer provides a robust solution for asymmetric assignment problems in sensor networks.
• The strategy offers significant improvements in energy balancing and overall network performance, particularly under varying node conditions.