A Distributed Multi-Hop Intra-Clustering Approach Based on Neighbors Two-Hop Connectivity for IoT Networks
| Autor: | Saad Harous, Zibouda Aliouat, Hakim Mabed, Mohamed Sofiane Batta |
|---|---|
| Přispěvatelé: | Franche-Comté Électronique Mécanique, Thermique et Optique - Sciences et Technologies (UMR 6174) (FEMTO-ST), Université de Technologie de Belfort-Montbeliard (UTBM)-Ecole Nationale Supérieure de Mécanique et des Microtechniques (ENSMM)-Université de Franche-Comté (UFC), Université Bourgogne Franche-Comté [COMUE] (UBFC)-Université Bourgogne Franche-Comté [COMUE] (UBFC)-Centre National de la Recherche Scientifique (CNRS), Université Ferhat-Abbas Sétif 1 [Sétif] (UFAS1), United Arab Emirates University (UAEU) |
| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
IoT
Computer science Distributed computing A* search algorithm 02 engineering and technology [INFO.INFO-SE]Computer Science [cs]/Software Engineering [cs.SE] lcsh:Chemical technology Biochemistry Article Analytical Chemistry law.invention [INFO.INFO-IU]Computer Science [cs]/Ubiquitous Computing [INFO.INFO-CR]Computer Science [cs]/Cryptography and Security [cs.CR] law Robustness (computer science) Default gateway Convergence (routing) 0202 electrical engineering electronic engineering information engineering lcsh:TP1-1185 Electrical and Electronic Engineering Cluster analysis Instrumentation Node (networking) 020206 networking & telecommunications Energy consumption multi-hop clustering WSN [INFO.INFO-MO]Computer Science [cs]/Modeling and Simulation Atomic and Molecular Physics and Optics Networking hardware [INFO.INFO-MA]Computer Science [cs]/Multiagent Systems [cs.MA] dynamic intra-clustering distributed clustering 020201 artificial intelligence & image processing [INFO.INFO-ET]Computer Science [cs]/Emerging Technologies [cs.ET] [INFO.INFO-DC]Computer Science [cs]/Distributed Parallel and Cluster Computing [cs.DC] |
| Zdroj: | Sensors Sensors, MDPI, 2021, 21 (3), pp.873. ⟨10.3390/s21030873⟩ Sensors (Basel, Switzerland) Sensors, Vol 21, Iss 873, p 873 (2021) Volume 21 Issue 3 |
| ISSN: | 1424-8220 |
| DOI: | 10.3390/s21030873⟩ |
| Popis: | International audience; 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. |
| Databáze: | OpenAIRE |
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