Weight based clustering in wireless sensor networks

Tandon, Ravi; Dey, Biswanath; Nandi, Sukumar

doi:10.1109/ncc.2013.6488034

Cited by 18 publications

(10 citation statements)

References 5 publications

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“…As shown in Table I, most WSN clustering techniques are based on homogeneous networks. Those supporting WSN heterogeneity focus mostly on energy resources [175], but in IoT, heterogeneity is somewhat different with respect to clustering:…”

Section: Migrating From Wsns To Iotmentioning

confidence: 99%

A Survey and Future Directions on Clustering: From WSNs to IoT and Modern Networking Paradigms

Shahraki

Taherkordi

Haugen

et al. 2021

IEEE Trans. Netw. Serv. Manage.

121

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Many Internet of Things (IoT) networks are created as an overlay over traditional ad-hoc networks such as Zigbee. Moreover, IoT networks can resemble ad-hoc networks over networks that support device-to-device (D2D) communication, e.g., D2D-enabled cellular networks and WiFi-Direct. In these ad-hoc types of IoT networks, efficient topology management is a crucial requirement, and in particular in massive scale deployments. Traditionally, clustering has been recognized as a common approach for topology management in ad-hoc networks, e.g., in Wireless Sensor Networks (WSNs). Topology management in WSNs and ad-hoc IoT networks has many design commonalities as both need to transfer data to the destination hop by hop. Thus, WSN clustering techniques can presumably be applied for topology management in ad-hoc IoT networks. This requires a comprehensive study on WSN clustering techniques and investigating their applicability to ad-hoc IoT networks. In this paper, we conduct a survey of this field based on the objectives for clustering, such as reducing energy consumption and load balancing, as well as the network properties relevant for efficient clustering in IoT, such as network heterogeneity and mobility. Beyond that, we investigate the advantages and challenges of clustering when IoT is integrated with modern computing and communication technologies such as Blockchain, Fog/Edge computing, and 5G. This survey provides useful insights into research on IoT clustering, allows broader understanding of its design challenges for IoT networks, and sheds light on its future applications in modern technologies integrated with IoT.

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Section: Migrating From Wsns To Iotmentioning

confidence: 99%

A Survey and Future Directions on Clustering: From WSNs to IoT and Modern Networking Paradigms

Shahraki

Taherkordi

Haugen

et al. 2021

IEEE Trans. Netw. Serv. Manage.

121

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“…Weight-based clustering (WBC) [15], [16] WBC calculation selects CH in such a way that CH consistently has the best remaining energy. Remaining energy is energy left in a node in the wake of playing out its preparing and data transferring functions.…”

Section: H Weight-based Clustering Protocolsmentioning

confidence: 99%

Numerous Clustering Techniques with Application and Limitations in Wireless Sensor Network

kushwaha*,

Amjad

2019

IJEAT

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Wireless Sensor Network (WSN) is a very common area to work with different technology which is very useful for real time application. There are various application works with the help of WSN .some of internet of things, machine learning, big data etc. in WSN there are four basic component of WSN that is sensing unit, transceiver unit, processing unit, and storage unit. Energy is the important critical design issue in WSN. By applying clustering approach we can save the energy and attain load balancing of a network. Sensor nodes are viewed as homogeneous since the looks into in the field of WSNs have been advanced, however, a few nodes might be of various energy levels and it is draw out the lifetime of a WSN and its unwavering quality. Clustering methods are required so that sensor networks can work long time with different area. In this paper, we discussed the various clustering techniques those are helpful to maximize the lifespan of WSN.

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“…It extends Low Energy Adaptive Clustering Hierarchy (LEACH) protocol [4] by using residual energy as primary parameter and intra-communication cost to cluster the network. HEED consumes a significant part of its energy for the process of clustering [5,6].…”

Section: Extension Of Leachmentioning

confidence: 99%

ArcRectZone: A Lightweight Curved Rectangle Vector Based Secure Routing for Mobile Ad-Hoc Sensor Network

Jebaseelan¹,

Srinivasan²

2017

IJIES

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Location aided routing in Mobile-Ad hoc networks are the most significant process because it limits the route search and allows routing with least messages. Due to the dynamic and uncertain infrastructure of Ad-hoc and sensor networks also creates several security issues like route misbehaviors. This paper aims to develop a new lightweight route selection scheme with the security concern. In this scheme, the routing attack targets are identified and avoided by deploying intellectual watchdog and lightweight key verification mechanisms, the scheme also utilizes the curved rectangle zone selection for shrinking route search space. The scheme is extended to adopt the curved rectangle zone routing for both Ad-hoc and Sensor Networks. The core functionality of the proposed work in terms of cost effective and secure route selection is validated by NS-2 tool. The experimental results demonstrated that the proposed approach is cost effective and secure and provides significant performance improvements with least energy consumption.

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Weight based clustering in wireless sensor networks

Cited by 18 publications

References 5 publications

A Survey and Future Directions on Clustering: From WSNs to IoT and Modern Networking Paradigms

A Survey and Future Directions on Clustering: From WSNs to IoT and Modern Networking Paradigms

Numerous Clustering Techniques with Application and Limitations in Wireless Sensor Network

ArcRectZone: A Lightweight Curved Rectangle Vector Based Secure Routing for Mobile Ad-Hoc Sensor Network

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