Optimal Energy Consumption Tasks Scheduling Strategy for Multi-Radio WSNs

Area of Science:

• Computer Science
• Electrical Engineering

Background:

• Multi-radio technology is key to enhancing Wireless Sensor Network (WSN) performance.
• Energy efficiency and extended network lifetime are critical for battery-operated Multi-Radio WSNs (MR-WSNs).

Purpose of the Study:

• To analyze energy consumption in MR-WSNs, focusing on transmission and idle listening.
• To develop an energy consumption model for multi-radio nodes.
• To propose an optimized task scheduling strategy for minimizing energy usage in MR-WSNs.

Main Methods:

• Analysis of transmitting and idle listening energy consumption in multi-radio nodes.
• Development of an energy consumption model for MR-WSN nodes.
• Implementation of a heuristic optimal energy consumption task scheduling strategy using the Particle Swarm Optimization (PSO) algorithm.

Main Results:

• The proposed PSO-based strategy effectively minimizes energy consumption in MR-WSNs.
• Experimental and simulation results demonstrate superior performance compared to other algorithms.
• The strategy shows improvements in network lifetime and task extensibility.

Conclusions:

• The developed energy consumption model and PSO-based scheduling strategy are effective for MR-WSNs.
• The proposed approach offers significant advantages in energy efficiency, network longevity, and adaptability.