DCOPA: a distributed clustering based on objects performances aggregation for hierarchical communications in IoT applications

Journal article

Mir, F. and Meziane, F. 2022. DCOPA: a distributed clustering based on objects performances aggregation for hierarchical communications in IoT applications. Cluster Computing. 26, p. 1077–1098. https://doi.org/10.1007/s10586-022-03741-w
AuthorsMir, F. and Meziane, F.
Abstract

Developing clustering algorithms for energy optimization, for the Internet of Things (IoT) applications based mainly on
wireless sensors networks services, is a major research challenge. The large amount of data generated by this type of
networks, requires a huge quantity of energy and a large number of Internet connections to support communication
between different devices via the Internet. Therefore, clustering protocols for data routing in IoT, also referred to as hierarchical routing protocols, need to take into account energy efficiency, the number of individual connections and scalability. In this paper, we propose a novel distributed clustering protocol based on the objects’ performances aggregation for hierarchical communications in IoT applications focused on Wireless Sensors Networks (WSNs) for the self election of Cluster Heads (CHs) and the clusters construction. Each node calculates a threshold T(i) considered as a competition timer to become a CH. A node can be a CH only once among a fixed number of rounds. An optimum number of clusters is computed based on the network parameters. Simulation results show that our proposed solution is better with energy management performance parameters compared to the Low Energy Adaptive Clustering Hierarchy (LEACH) protocol and two other developed energy-efficient protocols namely LEACH-MAC and TB-LEACH.

KeywordsInternet of Things; Wireless Sensors Networks; ; Clustering; ; Data communication
Year2022
JournalCluster Computing
Journal citation26, p. 1077–1098
PublisherSpringer
ISSN1386-7857
Digital Object Identifier (DOI)https://doi.org/10.1007/s10586-022-03741-w
Web address (URL)https://link.springer.com/article/10.1007/s10586-022-03741-w#citeas
Accepted author manuscript
File Access Level
Controlled
Output statusPublished
Publication dates
Online15 Sep 2022
Publication process dates
Accepted25 Aug 2022
Deposited22 Sep 2022
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Alshehri, H. and Meziane, F. 2014. The Effect of recommendations from family members and friends and third party endorsement in B2C E-Commerce: The case of Saudi Arabia. 24th International Business Information Management Association Conference - Crafting Global Competitive Economies: 2020 Vision Strategic Planning and Smart Implementation. Milan, Italy 06 - 07 Nov 2014 IBIMA.