Hierarchical Clustering for Dynamic and Heterogeneous Internet of Things

Kumar, Saurabh; Zaveri, Mukesh A.

doi:10.1016/j.procs.2016.07.211

Cited by 32 publications

(22 citation statements)

References 12 publications

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“…For evaluating algorithms in IoT environment, all communication should be performed using IoT stack, which is designed specifically for energy-constrained environment for Internet of Things [40][41][42][43]. IoT protocol stack is completely different from the normal WSN protocol stack [9,10,40]. The best part of the work is that the whole system is evaluated using Cooja simulator [32] for emulating actual IoT environment.…”

Section: Simulation Resultsmentioning

confidence: 99%

“…The generic architecture or reference model is too complex for one-to-one mapping for any real application. Earlier, IoT architecture [9,10] has been presented in an abstract way and evaluated to measure the performance. In practice, there is a need to integrate ordinary sensors or IoT devices with an application.…”

Section: Related Workmentioning

confidence: 99%

“…Moreover, the mobility of IoT nodes allows on the fly clustering with underlying sensor nodes dynamically in the region of interest, which is not possible in case of WSN. Further, in the literature, there is no method reported for clustering in IoT environment so far, and, for the first time, it is explored using the two-layer architecture in IoT as introduced in our earlier proposed work [9,10].…”

Section: Related Workmentioning

confidence: 99%

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Clustering Approaches for Pragmatic Two‐Layer IoT Architecture

Kumar

Zaveri

2018

Wireless Communications and Mobile Computing

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Connecting all devices through Internet is now practical due to Internet of Things. IoT assures numerous applications in everyday life of common people, government bodies, business, and society as a whole. Collaboration among the devices in IoT to bring various applications in the real world is a challenging task. In this context, we introduce an application-based two-layer architectural framework for IoT which consists of sensing layer and IoT layer. For any real-time application, sensing devices play an important role. Both these layers are required for accomplishing IoT-based applications. The success of any IoT-based application relies on efficient communication and utilization of the devices and data acquired by the devices at both layers. The grouping of these devices helps to achieve the same, which leads to formation of cluster of devices at various levels. The clustering helps not only in collaboration but also in prolonging overall network lifetime. In this paper, we propose two clustering algorithms based on heuristic and graph, respectively. The proposed clustering approaches are evaluated on IoT platform using standard parameters and compared with different approaches reported in literature.

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Section: Simulation Resultsmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

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Clustering Approaches for Pragmatic Two‐Layer IoT Architecture

Kumar

Zaveri

2018

Wireless Communications and Mobile Computing

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“…This shows a significant improvement in terms of delay, packet delivery ratio, and throughput and energy consumption. A dynamic heterogeneous clustering algorithm is proposed by considering features like connectivity, mobility, and communication . The cluster formation is done by considering the parameters like neighbor count and residual energy.…”

Section: Related Workmentioning

confidence: 99%

Load balanced fuzzy‐based unequal clustering for wireless sensor networks assisted Internet of Things

Agrawal

Pandey

2020

Engineering Reports

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The fundamental unit of the Internet of Things (IoT) is wireless sensor networks (WSNs). Due to their low cost and prospective use, WSNs have drawn interest in various applications over the last years. Since sensor nodes are equipped with limited battery, it is vital energy consumption be carefully monitored. Therefore, minimizing the node energy consumption is clearly essential to extend the network lifetime. In this paper, a fuzzy‐based unequal clustering protocol is proposed. Not only does the proposed protocol prolong the network lifetime, but it also balances the load among nodes. Former protocols do not consider load balancing. Fuzzy logic is employed considering four inputs: residual energy, distance to a base station, node degree and centrality. To validate its efficiency, the novel protocol is compared with other relevant protocols. The obtained results prove that the protocol here proposed outperforms other state‐of‐the‐art protocols.

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“…A dynamic heterogeneous clustering for internet‐of‐things (IoTs) takes into consideration mobility, communication, and connectivity among sensor devices. For the last 10 years, IoT is a point of great interest not only for academic institutions, but also industrial sectors . Creation of a world in which devices can interact with each other and work according to the instructions of users is the purpose of IoTs.…”

Section: Introductionmentioning

confidence: 99%

Energy efficient scalability of three level hexagonal heterogeneous broad transmission distance protocol (3L‐HEXA‐HTBTDP) for WSN‐IoT networks

Shrivastav

Kulat

2018

Int J Communication

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Summary Multilevel heterogeneity is the present demand of wireless sensor networks as well as internet‐of‐things for balanced energy consumption of the network systems. In this paper, three level hexagonal heterogeneous broad transmission distance protocol (3L‐HEXA‐HTBTDP) is introduced for increasing the energy efficiency of the network. Normal, advanced, and superadvanced sensor nodes in a hexagonal field represent three level heterogeneity. These nodes are elected as cluster heads (CHs) on the basis of new thresholds, thus transferring the collected data to the base station. The protocol is beneficial in cellular communication and web‐of‐things applications to fulfill the high energy requirements of the wireless systems. The scalability is done here for perceiving the differences in the application of proposed algorithm 3L‐HEXA‐HTBTDP on different number of sensor nodes with variable values of initial energies. This is a promising approach to achieve reliable communication, coverage, and connectivity among sensor nodes of the hexagonal field. The scheme is evaluated through exhaustive simulation using Matlab. It is compared with the previous approaches of clustering implemented on the hexagonal field. Different performance parameters like alive node metrics, stability period, network lifetime, residual energy, and variance of energy are used for benchmarking the results of 3L‐HEXA‐HTBTDP with three level hexagonal stable election protocol (3L‐HEXA‐SEP) and three level hexagonal energy efficient heterogeneous clustered scheme (3L‐HEXA‐EEHC). In general, it is observed that the proposed 3L‐HEXA‐HTBTDP outperforms other existing protocols.

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Hierarchical Clustering for Dynamic and Heterogeneous Internet of Things

Cited by 32 publications

References 12 publications

Clustering Approaches for Pragmatic Two‐Layer IoT Architecture

Clustering Approaches for Pragmatic Two‐Layer IoT Architecture

Load balanced fuzzy‐based unequal clustering for wireless sensor networks assisted Internet of Things

Energy efficient scalability of three level hexagonal heterogeneous broad transmission distance protocol (3L‐HEXA‐HTBTDP) for WSN‐IoT networks

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