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Hierarchical routing protocols for wireless sensor network: a compressive survey

journal contribution
posted on 2024-11-02, 12:30 authored by Hiu Fai Chan, Karina Mabell Gomez Chavez, Heiko Rudolph, Akram HouraniAkram Hourani
Wireless sensor networks (WSNs) are one of the key enabling technologies for the internet of things (IoT). WSNs play a major role in data communications in applications such as home, health care, environmental monitoring, smart grids, and transportation. WSNs are used in IoT applications and should be secured and energy efficient in order to provide highly reliable data communications. Because of the constraints of energy, memory and computational power of the WSN nodes, clustering algorithms are considered as energy efficient approaches for resource-constrained WSNs. In this paper, we present a survey of the state-of-the-art routing techniques in WSNs. We first present the most relevant previous work in routing protocols surveys then highlight our contribution. Next, we outline the background, robustness criteria, and constraints of WSNs. This is followed by a survey of different WSN routing techniques. Routing techniques are generally classified as flat, hierarchical, and location-based routing. This survey focuses on the deep analysis of WSN hierarchical routing protocols. We further classify hierarchical protocols based on their routing techniques. We carefully choose the most relevant state-of-the-art protocols in order to compare and highlight the advantages, disadvantage and performance issues of each routing technique. Finally, we conclude this survey by presenting a comprehensive survey of the recent improvements of low-energy adaptive clustering hierarchy routing protocols and a comparison of the different versions presented in the literature.

History

Journal

Wireless Networks

Volume

26

Issue

5

Start page

3291

End page

3314

Total pages

24

Publisher

Springer

Place published

United States

Language

English

Copyright

© 2020, Springer Science+Business Media, LLC, part of Springer Nature.

Former Identifier

2006097201

Esploro creation date

2020-09-08

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