A novel energy-efficient scheduling method for three-dimensional heterogeneous wireless sensor networks based on improved memetic algorithm and node cooperation strategy

Abstract

Nodes in performance heterogeneous wireless sensor networks (HWSNs) often have varying levels of available energy, storage space, and processing power due to the network’s limited resources. Additionally, coverage redundancy and channel conflicts may adversely influence the quality of service in a network when many nodes have been deployed at once. Energy as a major constrained resource requires an effective energy-efficient scheduling mechanism to balance node energy consumption to extend the network lifespan. Therefore, this research proposes an energy-efficient scheduling technique, IMA–NCS-3D for three-dimensional HWSNs on the basis of an improved memetic algorithm and node cooperation strategy. A multi-objective fitness function is created to encode the active and inactive states of nodes as genes, and the optimal scheduling set of the network is built via selection, crossover, variation, and local search. This phase of the process is known as node scheduling. Node-to-node cooperation solutions are offered during data transmission to deal with unforeseen traffic abnormalities and reduce congestion and channel conflicts when traffic volumes are high. Simulation results show that IMA–NCS-3D has superior scheduling capability, cross-network load balancing capability, and a longer network lifespan than other current coverage optimization approaches.