LEACH Protocol Optimization Based on Weighting Strategy and the Improved Ant Colony Algorithm

Area of Science:

• Computer Science
• Electrical Engineering
• Network Engineering

Background:

• Wireless Sensor Networks (WSNs) face energy consumption challenges.
• Existing Low-Energy Adaptive Clustering Hierarchy (LEACH) protocols suffer from randomness and local optimum issues in path optimization.

Purpose of the Study:

• To address the limitations of current LEACH protocols in WSNs.
• To propose an optimized LEACH protocol using novel algorithms for improved performance.

Main Methods:

• Proposed an Optimal Combined Weighting (OCW) method for selecting cluster heads based on residual energy, density, and distance to the sink.
• Implemented an Improved Ant Colony Optimization (IACO) algorithm for optimizing transmission paths within clusters.
• Introduced a dynamic replacement mechanism for cluster head nodes to reduce network energy consumption.

Main Results:

• The OCW method enhances the quality of selected cluster head nodes.
• IACO optimizes network partitioning and inter-cluster transmission paths.
• Simulations demonstrate improved network energy efficiency and path optimization compared to standard LEACH.

Conclusions:

• The proposed OCW and IACO algorithms effectively optimize the LEACH protocol for WSNs.
• The enhanced LEACH protocol offers significant improvements in energy efficiency and path selection.
• The method provides a viable solution for prolonging the operational life of WSNs.