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Energy Efficiency Routing Algorithms in IoT: A Survey

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Proceedings of the 8th International Conference on Advanced Intelligent Systems and Informatics 2022 (AISI 2022)

Part of the book series: Lecture Notes on Data Engineering and Communications Technologies ((LNDECT,volume 152))

Abstract

Internet of Things (IoT) is a new paradigm. IoT consists of a complex network of smart devices that frequently exchange data over the Internet. The aim of IoT is to make everything in our world under control and also keeping them up-to-date about the state of the things. IoT devices sense the environment and send the obtained information to the Internet cloud without the necessity of human-to-human or human-to-machine connection. Wireless sensors have limited energy resources due to the use of batteries to supply energy, and since it is usually not possible to replace the batteries of these sensors. In addition, the lifespan of the Wireless Sensor Network (WSN) is limited and short. Therefore, reducing the energy consumption of sensors in IoT networks for increasing network lifespan is one of the fundamental challenges and issues in these networks. The literature included here provides an overview of some of the most current research methodologies about the most popular protocols. Also, this paper identifies the major Machine learning (ML) models and bio-inspired algorithms for reducing energy consumption in IoT and a discussion on the evaluation of their effectiveness in energy consumption prediction and expanding network life.

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Author information

Authors and Affiliations

  1. Faculty of Engineering, Suez Canal University, Ismailia, Egypt

    Marwa Gamal

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  1. Marwa Gamal
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Correspondence to Marwa Gamal .

Editor information

Editors and Affiliations

  1. Faculty of Computers Artificial Intelligence, Cairo University, Giza, Egypt

    Aboul Ella Hassanien

  2. Faculty of Electrical Engineering and Computer Science, VÅ B-Technical University of Ostrava, Ostrava-Poruba, Moravskoslezsky, Czech Republic

    Václav Snášel

  3. International Center for Informatics Research, Beijing Jaiotong University, Beijing, China

    Mincong Tang

  4. College of Computer Science and Mathematics, Fujian University of Technology, Fuzhou, Fujian, China

    Tien-Wen Sung

  5. Fujian University of Technology, New Taipei, Taiwan

    Kuo-Chi Chang

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Gamal, M. (2023). Energy Efficiency Routing Algorithms in IoT: A Survey. In: Hassanien, A.E., Snášel, V., Tang, M., Sung, TW., Chang, KC. (eds) Proceedings of the 8th International Conference on Advanced Intelligent Systems and Informatics 2022. AISI 2022. Lecture Notes on Data Engineering and Communications Technologies, vol 152. Springer, Cham. https://doi.org/10.1007/978-3-031-20601-6_55

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