An Energy-Efficient Hybrid Clustering Technique (EEHCT) for IoT-Based Multilevel Heterogeneous Wireless Sensor Networks

Abstract

Internet-of-Things (IoT)-based Heterogeneous Wireless Sensor Network (HWSN) has emerged as a prevalent technology that plays a significant role in developing various human-centric applications. Like in a wireless sensor network (WSN), energy is also the most crucial resource in IoTbased HWSN. The researchers have proposed many works to achieve energy-efficient network operations by minimizing energy usage. A vast proportion of these works emphasize using the clustering approach, which has proved its worth to a great extent. However, most schemes require the repeated formation of clusters incurring a significant amount of nodes' energy in the clustering process. The protocol design of such schemes also varies with the changing levels of heterogeneity. In this work, a hybrid clustering scheme-An Energy-Efficient Hybrid Clustering Technique (EEHCT) has been proposed for IoT-based HWSN that minimizes the energy consumption in clusters' formation and distributes the network load evenly irrespective of the heterogeneity level to prolong network lifetime. It appropriately utilizes dynamic and static clustering strategies to formulate the load-balanced clusters in the network. EEHCT establishes its supremacy over state-of-the-art schemes via an extensive set of simulations and experimentation in terms of multiple network performance metrics like stability, throughput, and network lifetime. Like, it achieves a gain up to 90.27% with respect to network lifetime over its peers in the standard operating conditions and under varying network configurations. In addition to quantitative analysis, a statistical analysis has also been provided to demonstrate the formation of energy-balanced clusters through the proposed scheme.

Artificial Intelligence-based Cayley Menger Securex-means Clustering and Hyper Gradient Reliable Data Transmission in Wsn

“…It is obviously seen which CMX-HGDTNE technique gives improved performance upon comparison by two other methods. 𝐸𝐶 of the CMX-HGDTNE method is reduced by 15% and 25% when compared to [1] and [2].…”

“…For the simulation setup, the sensor nodes are taken from 50 to 500. The efficacy of the CMX-HGDTNE method in secure data transmission is shown by comparing the experimental outcomes of two conventional techniques such as the Energy-Efficient Hybrid Clustering Technique (EEHCT) [1] and multifunctional and privacy-preserving outsourcing computation [2] regarding four different crucial metrics. During experiment conduction, the research work takes 500 sensor nodes as input and carries out the secure cluster formation and reliable data transmission simultaneously.…”

“…Figure 5 and Table 2 depict energy consumption with respect to distinct sensor odes ranging between 50 and 500. When taking 200 number of SN as input, the CMX-HGDTNE method, [1], and [2] consume 30J, 35.45J and 40J respectively. Regarding 250 input SN, CMX-HGDTNE method, [1], and [2] perform data communication process with 30 J, 35.85J, and 39J energy consumption.…”

An energy‐aware software fault detection system based on hierarchical rule approach for enhancing quality of service in internet of things‐enabled wireless sensor network

“…Designing a high-performance WSN is the key factor that guarantees the completion of several sensing tasks. 6 With the integration of these high-performance WSNs, there has been a proliferation of IoT applications. Whether the events occurred remotely or nearby, the IWSNs have penetrated numerous real-time applications like smart industry, medical monitoring, precision agriculture, military surveillance, and weather monitoring.…”

“…In recent decades, WSNs and data acquisition schemes have progressed rapidly with the IoT owing to various challenges and restrictions. Designing a high‐performance WSN is the key factor that guarantees the completion of several sensing tasks 6 . With the integration of these high‐performance WSNs, there has been a proliferation of IoT applications.…”