A Scalable K-hop Clustering Algorithm for Pseudolinear MANET

Ahmed, Tanjil; Abdur, Md.; Zaman, Ambreen; Amjad, Mahfida

doi:10.5120/ijca2018916891

Cited by 1 publication

(1 citation statement)

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“…Therefore, direct communication becomes obstructive and k-hop intra-clustering communication should be applied to ensure the network scalability. The k-hop intra-clustering model received a considerable interest from the research community [ 17 , 18 , 19 ] since it expresses (in a better way) the features of well-organized network. Indeed, k-hops intra-clustering model reduces the number of clusters which reduces the number of long-range communication channels and increases network durability [ 9 ].…”

Section: Introductionmentioning

confidence: 99%

A Distributed Multi-Hop Intra-Clustering Approach Based on Neighbors Two-Hop Connectivity for IoT Networks

Batta

Mabed

Aliouat

et al. 2021

Sensors

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Under a dense and large IoT network, a star topology where each device is directly connected to the Internet gateway may cause serious waste of energy and congestion issues. Grouping network devices into clusters provides a suitable architecture to reduce the energy consumption and allows an effective management of communication channels. Although several clustering approaches were proposed in the literature, most of them use the single-hop intra-clustering model. In a large network, the number of clusters increases and the energy draining remains almost the same as in un-clustered architecture. To solve the problem, several approaches use the k-hop intra-clustering to generate a reduced number of large clusters. However, k-hop proposed schemes are, generally, centralized and only assume the node direct neighbors information which lack of robustness. In this regard, the present work proposes a distributed approach for the k-hop intra-clustering called Distributed Clustering based 2-Hop Connectivity (DC2HC). The algorithm uses the two-hop neighbors connectivity to elect the appropriate set of cluster heads and strengthen the clusters connectivity. The objective is to optimize the set of representative cluster heads to minimize the number of long range communication channels and expand the network lifetime. The paper provides the convergence proof of the proposed solution. Simulation results show that our proposed protocol outperforms similar approaches available in the literature by reducing the number of generated cluster heads and achieving longer network lifetime.

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Section: Introductionmentioning

confidence: 99%