An Effective Hybrid Routing Algorithm in WSN: Ant Colony Optimization in combination with Hop Count Minimization

Area of Science:

• Computer Science
• Electrical Engineering
• Network Engineering

Background:

• Wireless Sensor Networks (WSNs) require routing protocols balancing cost, reliability, and maintenance.
• Existing Ant Colony Optimization (ACO) and minimum hop count algorithms have limitations in energy efficiency and dynamic topology handling.
• Critical WSN factors include energy constraints, load balancing, and dynamic topology.

Purpose of the Study:

• To develop a novel hybrid routing algorithm for WSNs.
• To address energy constraints, network load balancing, and dynamic topology maintenance.
• To improve upon existing ACO-based and minimum hop count routing algorithms.

Main Methods:

• Investigated strengths and weaknesses of existing ACO-based and minimum hop count WSN routing algorithms.
• Proposed a hybrid routing algorithm integrating ACO and minimum hop count.
• Implemented the WSN model and proposed algorithm using C++ for simulations.

Main Results:

• The hybrid algorithm finds optimal routing paths with minimal total and balanced energy consumption.
• Demonstrated superiority in optimal path searching, load balancing, and topology maintenance.
• Outperformed other WSN routing algorithms in convergence rate, global optimal solution success rate, and network lifetime.

Conclusions:

• The proposed hybrid routing algorithm effectively optimizes energy consumption and extends network lifetime in WSNs.
• The integration of ACO and minimum hop count offers unique advantages for WSN routing.
• Simulation results validate the algorithm's superior performance in key WSN metrics.