An Elite Hybrid Particle Swarm Optimization for Solving Minimal Exposure Path Problem in Mobile Wireless Sensor...

Area of Science:

• Computer Science
• Electrical Engineering
• Network Security

Background:

• Mobile wireless sensor networks (MWSNs) enhance coverage quality for monitored regions.
• Minimal exposure path (MEP) is crucial for assessing sensor network vulnerabilities.
• Static sensor networks face coverage issues due to sensor failures.

Purpose of the Study:

• To address the challenge of finding minimal exposure paths in mobile wireless sensor networks (MWSNs).
• To develop an efficient algorithm for the MMEP problem in dynamic sensor environments.

Main Methods:

• Formulated the minimal exposure path problem for MWSNs (MMEP).
• Transformed the MMEP problem into a high-dimensional, non-differentiable, non-linear numerical functional extreme problem.
• Proposed the HPSO-MMEP algorithm, integrating genetic algorithms with particle swarm optimization.

Main Results:

• The HPSO-MMEP algorithm demonstrated suitability for the converted MMEP problem.
• Experimental simulations showed superior performance of HPSO-MMEP compared to existing algorithms.
• Validated the effectiveness of the proposed algorithm across various MWSN topologies.

Conclusions:

• The HPSO-MMEP algorithm offers an efficient solution for identifying critical paths in MWSNs.
• This research contributes to enhancing the security and robustness of mobile wireless sensor networks.
• The findings are valuable for network designers seeking to improve sensor network vulnerability assessment.