Dynamic Layered Dual-Cluster Heads Routing Algorithm Based on Krill Herd Optimization in UWSNs

Jiang, Peng; Feng, Yang; Wu, Feng; Shu, Yu; Xu, Hao

doi:10.3390/s16091379

Cited by 9 publications

(3 citation statements)

References 9 publications

(10 reference statements)

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“…They use the CHs degree to construct a cluster, and it is incapable of managing the load sensor nodes among CH. [30] proposed a well dynamically layer dual-CHs routing method based on the Krill herds (KH) used in underwater WSN. The main aim is to keep track of how much electricity CHs use.…”

Section: Related Workmentioning

confidence: 99%

“…As is well known, data communication consumes more energy than data sensing and processing. As illustrated [30], this work adopts the first order in the radio model to represent energy usage in nodes. If another packet contains kb bits of data, the energy consumes for transmitting kb bits of ETX data and retrieving kb bits of data ERX can be written as follows:…”

Section: Sensor Node Neighborhood Set Constructionmentioning

confidence: 99%

See 1 more Smart Citation

Wireless Network Security Using Load Balanced Mobile Sink Technique

Alkanhel¹,

Abouhawwash²,

Sangeethaa³

et al. 2023

Intelligent Automation &Amp; Soft Computing

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Section: Related Workmentioning

confidence: 99%

Section: Sensor Node Neighborhood Set Constructionmentioning

confidence: 99%

Wireless Network Security Using Load Balanced Mobile Sink Technique

Alkanhel¹,

Abouhawwash²,

Sangeethaa³

et al. 2023

Intelligent Automation &Amp; Soft Computing

View full text Add to dashboard Cite

“…Anyways, they utilize the CHs degree in the formation of a cluster, and it cannot manage the load of SNs (sensor nodes) between CHs. In [26], introduced the wellknown algorithm as dynamic layered dual-CHs routing based on the optimization of Krill herd (KH) in underwater wireless-sensor networks (UWSNs). The main purpose of this algorithm is to manage the power consumption of CHs.…”

Section: Literature Surveymentioning

confidence: 99%

Lifetime centric load balancing mechanism in wireless sensor network based IoT environment

Veerabadrappa¹,

Marikannan

2021

IJECE

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Wireless sensor network (WSN) is a vital form of the underlying technology of the internet of things (IoT); WSN comprises several energy-constrained sensor nodes to monitor various physical parameters. Moreover, due to the energy constraint, load balancing plays a vital role considering the wireless sensor network as battery power. Although several clustering algorithms have been proposed for providing energy efficiency, there are chances of uneven load balancing and this causes the reduction in network lifetime as there exists inequality within the network. These scenarios occur due to the short lifetime of the cluster head. These cluster head (CH) are prime responsible for all the activity as it is also responsible for intra-cluster and inter-cluster communications. In this research work, a mechanism named lifetime centric load balancing mechanism (LCLBM) is developed that focuses on CH-selection, network design, and optimal CH distribution. Furthermore, under LCLBM, assistant cluster head (ACH) for balancing the load is developed. LCLBM is evaluated by considering the important metrics, such as energy consumption, communication overhead, number of failed nodes, and one-way delay. Further, evaluation is carried out by comparing with ES-Leach method, through the comparative analysis it is observed that the proposed model outperforms the existing model.

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