A cooperative optimization method for coverage and scheduling of traffic WSN relay nodes considering carbon emission cost constraints

Against the backdrop of the green and low-carbon transformation of traffic sensing systems, the high energy consumption and carbon emissions of relay nodes in wireless sensor networks are becoming increasingly prominent. To control the carbon emission costs of relay node operation while ensuring coverage quality, this paper proposes a collaborative optimization method for coverage and scheduling of wireless sensor network relay nodes considering carbon emission cost constraints. First, a coverage model and mathematical framework coupling "energy consumption - carbon emission - coverage efficiency" are established, integrating multi-objective optimization objectives and multiple constraints. Second, a multi-stage coverage optimization algorithm jointly evaluating carbon penalties and coverage gains is designed. Finally, a collaborative strategy combining carbon budget allocation and dynamic scheduling is proposed. Experiments show that the method converges in 40 out of 100 iterations, achieving a final coverage rate of 92%, which is 9% higher than the multi-objective differential evolution algorithm (83%) and the multi-objective particle swarm optimization algorithm (75%). The lifecycle carbon emissions under medium traffic density are 147. Compared to the comparative method, this method reduces CO ₂ emissions by more than 36g, while maintaining a data transmission success rate of 94% to 96%. This method provides a new solution for the efficient and low-carbon operation of green transportation sensing systems.