The Hexagonal Hierarchical Broad Telecommunication Length Protocol's (Hexa-Htbtdp) Scalability in Wsn-Iot Networks

Clustering applications for WSN-IoT must prioritize energy efficiency. It is not feasible to evaluate the lifespan of a network in the absence of clustering or variation. In order to create clustering algorithms that consume less energy, cluster head selection models have been used. It is a huge undertaking to simulate a whole WSN-IoT cluster. In this paper, we examine the dependability of the clustering mechanism and the durability of the network. Most of the research on energy-efficient clustering algorithms has been done in academic journals. To comprehend the energy efficiency of a sensor network, one must be aware of its initial energy sources, the quantity of data-collecting nodes, and the network field. Live node metrics, network durability, stability, and instability are performance indicators. More characteristics could be included in a comprehensive energy-efficient clustering model. A wide range of sensor nodes are used to investigate heterogeneous clustering in networks of varying sizes and kinds. In this study, we examine the scalability and heterogeneity of WSN-IoT clustering. Lifespan sub-periods display the living metrics used to assess energy-efficient clustering methods. Our first area of interest will be the two-level heterogeneity component of cluster head selection. A new protocol for heterogeneous hexagonal wide transmission distance (HEXA-HTBTDP). Different from a three-level protocol, which may have either advanced or super advanced nodes, a two-level heterogeneous protocol can have either normal or advanced nodes. By outperforming HEXA-SEP by 69.34% and HEXA-EEHC by 38.47% in terms of stability period, the suggested method’s algorithm proves to be very efficient. The proposed method has an 85% longer stability period and a 45.67% of longer lifespan than other Models.