Prolonging IoT Sensor Networks Lifetime for Different Smart City Applications Utilizing a Three-dimension MPA Based Fitness Function

This paper introduces a Three-dimension MPA Based Fitness Function (TDFF-MPA) protocol for the Internet of Things (IoT) networks. The protocol’s dual objectives are to lessen energy consumption and extend the network’s longevity, which have become critical priorities in the IoT due to the limitations of energy-constrained Sensor Nodes (SNs). TDFF-MPA achieves these objectives by dividing the rectangular sensory network region into a dynamic number of identical hexagonal clusters, with each cluster selecting its Cluster Head (CH) using the marine predator algorithm, which optimizes a clustering fitness function based on three key routing metrics: the intra-cluster distance, the remaining energy of SNs, and their distance from the sink node. To further eliminate setup overhead, the selected $\mathbf{C H}$ remains active for multiple rounds (batch-based) until its energy is inferior to a predetermined threshold. During data transmission, a CH aggregates data from SNs and routes it directly to the sink node. The simulation results are promising, showing that TDFF-MPA not only surpasses its counterparts in extending network longevity but also excels in energy conservation.