THWSN: Enhanced Energy-Efficient Clustering Approach for Three-Tier Heterogeneous Wireless Sensor Networks

Kumar, Nitin; Rani, Preeti; Kumar, Vinod; Athawale, Shashikant V.; Koundal, Deepika

doi:10.1109/jsen.2022.3200597

Cited by 32 publications

(19 citation statements)

References 49 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The data exchange between the network and the base station is facilitated by allowing multihop routing among the CHs. Kumar et al [61] proposed another dynamic clusteringbased scheme for the 3-tier HWSN under the title, THWSN: Enhanced Energy-Efficient Clustering Approach for Three-Tier HWSN. In [61], the authors have attempted to improve the network lifetime via careful selection of the cluster heads in the network.…”

Section: Related Workmentioning

confidence: 99%

“…Kumar et al [61] proposed another dynamic clusteringbased scheme for the 3-tier HWSN under the title, THWSN: Enhanced Energy-Efficient Clustering Approach for Three-Tier HWSN. In [61], the authors have attempted to improve the network lifetime via careful selection of the cluster heads in the network. [61] formulates three different probabilistic formulae to assist the nodes in their respective sensor classesstandard, intermediate, and advanced sensors in deciding upon the role of cluster heads.…”

Section: Related Workmentioning

confidence: 99%

“…In [61], the authors have attempted to improve the network lifetime via careful selection of the cluster heads in the network. [61] formulates three different probabilistic formulae to assist the nodes in their respective sensor classesstandard, intermediate, and advanced sensors in deciding upon the role of cluster heads. Moreover, in the formulation of type-based (based on nodes' type) threshold equations, nodes' remaining energy and their distances from the BS are the main selection criteria.…”

Section: Related Workmentioning

confidence: 99%

See 2 more Smart Citations

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

et al. 2023

View full text Add to dashboard Cite

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.

show abstract

Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

See 1 more Smart Citation

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

et al. 2023

View full text Add to dashboard Cite

show abstract

“…EEECA-THWSN [ 24 ] considers three-tier heterogeneity in WSNs which consists of standard, intermediate, and advanced SNs. Standard SNs have lower initial energy than intermediate SNs, and intermediate SNs have lower initial energy than advanced SNs.…”

Section: Related Workmentioning

confidence: 99%

An Innovative Clustering Hierarchical Protocol for Data Collection from Remote Wireless Sensor Networks Based Internet of Things Applications

Shah

Abbas

et al. 2023

Sensors

View full text Add to dashboard Cite

Recently, unmanned aerial vehicles (UAVs) have emerged as a viable solution for data collection from remote Internet of Things (IoT) applications. However, the successful implementation in this regard necessitates the development of a reliable and energy-efficient routing protocol. This paper proposes a reliable and an energy-efficient UAV-assisted clustering hierarchical (EEUCH) protocol designed for remote wireless sensor networks (WSNs) based IoT applications. The proposed EEUCH routing protocol facilitates UAVs to collect data from ground sensor nodes (SNs) that are equipped with wake-up radios (WuRs) and deployed remotely from the base station (BS) in the field of interest (FoI). During each round of the EEUCH protocol, the UAVs arrive at the predefined hovering positions at the FoI, perform clear channel assignment, and broadcast wake-up calls (WuCs) to the SNs. Upon receiving the WuCs by the SNs’ wake-up receivers, the SNs perform carrier sense multiple access/collision avoidance before sending joining requests to ensure reliability and cluster-memberships with the particular UAV whose WuC is received. The cluster-member SNs turn on their main radios (MRs) for data packet transmission. The UAV assigns time division multiple access (TDMA) slots to each of its cluster-member SNs whose joining request is received. Each SN must send the data packets in its assigned TDMA slot. When data packets are successfully received by the UAV, it sends acknowledgments to the SNs, after which the SNs turn off their MRs, completing a single round of the protocol. The proposed EEUCH routing protocol with WuR eliminates the issue of cluster overlapping, improves the overall performance, and increases network stability time by a factor of 8.7. It also improves energy efficiency by a factor of 12.55, resulting in a longer network lifespan compared to Low Energy Adaptive Clustering Hierarchy (LEACH) protocol. Moreover, EEUCH collects 5.05 times more data from the FoI than LEACH. These results are based on simulations in which the EEUCH protocol outperformed the existing six benchmark routing protocols proposed for homogeneous, two-tier, and three-tier heterogeneous WSNs.

show abstract

“…In addition, the current models impose additional computational burden when partitioning entire networks and also have weak reliability (i.e., the load-balancing method) when it involves delivering cutting-edge workflow applications that need quality of service (QoS) guarantees [13], [14]. As a result, after a particular number of rounds are complete, there are energy imbalance problems inside the network [15], [16].…”

Section: Introductionmentioning

confidence: 99%

Energy aware reliable routing model for sensor network enabled internet of things environment

Mysuru Srikantha,

Kuzhalvaimozhi,

Mallikarjun Silli

et al. 2023

IJEECS

View full text Add to dashboard Cite

Wireless sensor networks (WSNs), which are facilitated by the internet of things (IoTs), can be difficult to improve the lifespan of the network target area. Although the hotspot issue (i.e., the cluster head closest to the base station fails quickly) is mitigated by the clustered-based routing technique, it still has an important effect on the network's lifespan and target area. However, improper distribution of load between cluster heads has been shown to negatively impact network lifespan efficiency, so even though unequal clusters have been utilized successfully to tackle the hotspot issue, further work is needed. This study provides an energy-aware reliable routing (EARR) model for resolving the hotspot as well as load balancing issues simultaneously. To extend the lifespan of the network, the EARR model effectively minimizes energy consumption by the cluster heads using enhanced multi-objective optimization parameters. Further, EARR provides improved routing optimization metrics to improve data delivery with energy efficiency, less delay, and packet loss. The results of the experiments demonstrate that the EARR model provides excellent throughput and lifespan efficiency with low delay and communication overhead.

show abstract

THWSN: Enhanced Energy-Efficient Clustering Approach for Three-Tier Heterogeneous Wireless Sensor Networks

Cited by 32 publications

References 49 publications

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

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

An Innovative Clustering Hierarchical Protocol for Data Collection from Remote Wireless Sensor Networks Based Internet of Things Applications

Energy aware reliable routing model for sensor network enabled internet of things environment

Contact Info

Product

Resources

About