Sensor Node Activation Using Bat Algorithm for Connected Target Coverage in WSNs

Area of Science:

• Computer Science
• Electrical Engineering
• Artificial Intelligence

Background:

• Nature-inspired algorithms (NIAs) are effective for optimization problems.
• Wireless sensor networks (WSNs) face challenges in target coverage and energy efficiency.
• Existing methods often use a binary sensing model, which is less practical.

Purpose of the Study:

• To propose a sensor node activation method for target coverage using NIAs.
• To enhance energy efficiency and network lifetime in WSNs.
• To introduce a probabilistic sensing model for more realistic coverage.

Main Methods:

• Formulating the sensor target coverage problem as an objective function.
• Applying the bat algorithm (BA), a type of NIA.
• Introducing a 'bat couple' concept for coordinated sensing and data forwarding.
• Utilizing a probabilistic sensing model instead of a binary one.

Main Results:

• The proposed bat couple method ensures connectivity from active sensors to the sink.
• The probabilistic sensing model provides a more realistic approach to target detection.
• Simulation results demonstrate superior performance in terms of network lifetime compared to other methods.

Conclusions:

• The bat couple approach effectively addresses the sensor node activation problem.
• The probabilistic sensing model improves the practical applicability of coverage algorithms.
• This method offers significant improvements in WSN energy efficiency and longevity.