Clustering-Cum-Classification Based Machine Learning Medium Access Control Protocol for Three Tier Heterogeneous Wireless Sensor Network

A cluster cum classification hierarchical bit map assisted (CCHBMA) medium access control (MAC) protocol is proposed for the energy-efficient data transmission of wireless sensor networks. The proposed protocol utilizes the advantages of clustering and classification techniques to group similar nodes and efficiently allocate the wireless medium. The hierarchical bit mapping approach is used to provide aggregation-aware data transmission across the network. The dynamic scheduling algorithm adapts to changing the network conditions to improve the network performance. The proposed MAC protocol is evaluated based on simulation analysis and analytical modeling. The performance is compared to existing MAC protocols. The result analysis shows that the proposed MAC protocol shows significant improvement in energy-saving with respect to the existing protocols without compromising the packet delivery ratio.