Research of methods of increasing energy efficiency for the Internet оf Things (IoT) networks

DOI: 10.31673/2412-9070.2022.012630

Abstract

 The last decade has seen an increase in the number of Internet-enabled devices. The Internet of Things (IoT) is becoming more common in everyday life, bringing together more and more diverse physical objects. The key vision of IoT is to enable the interaction of a huge number of smart devices, together, in an integrated and interconnected heterogeneous network. The framework of the IoT is based on several enabling technologies including WSNs, cloud computing, machine learning, and peer-topeer systems. WSN is the most crucial part of the communication process of the IoT networks. In WSNs, sensor nodes capable of detecting the required information, performing some processing and communicating with other connected nodes are the main component of these networks. However, the life of these nodes is often restricted by being powered by a battery with a limited life, constraining processing ability, memory, and radio communications. Energy efficiency is one of the most crucial issues for WSNs. Most of the energy is consumed in data processing and transmissions. Therefore, in the article, the author makes a brief digression on the history and evolution of the Internet. Next, the article highlights the technologies on which IoT is based and establishes the fact that wireless sensor network (WSN) is one of the important elements of IoT, describes the relationship between WSN and the Internet of Things. In general, the article is devoted to the study of the development of energy efficiency methods for WSN. After identifying the sources of energy losses, this article discusses studies that test the most relevant methods of minimizing energy consumption IoT and WSN. The article also summarizes and recommends a wide range of energy efficient methods that will help in future research.

Keywords: Internet of Things (IoT); communications; energy consumption; wireless sensor networks (WSN); energy optimization; heterogeneous network; gate; sensor; clustering.

References
1. IoT Reliability: A Review Leading to 5 Key Research Directions / S. J. Moore, C. Nugent, S. Zhang, I. Cleland // CCF Trans. Pervasive Comput. Interact. 2020. №2. Р. 147–163.
2. Davis G. 2020 Life With 50 Billion Connected Devices // In Proceedings of the 2018 IEEE International Conference on Consumer Electronics (ICCE). Las Vegas, NV, USA, 12–15 January 2018.
3. Q.T.H. An Efficient Load Balancing Scheme of Energy Gauge / M. Adil, R. Khan, M. A. Almaiah [et al.] // Nodes to Maximize the Lifespan of Constraint Oriented Networks. 2020. №8. H. 148510–148527.
4. A Survey of Communication Protocols for Internet of Things and Related Challenges of Fog and Cloud Computing Integration / J. Dizdareviundefined, F. Carpio, A. Jukan, X. Masip-Bruin // ACM Comput. Surv. 2019. №51. P. 1–29.
5. MAC-AODV Based Mutual Authentication Scheme / M. Adil, R. Khan, M. A. Almaiah [et al.] // Constraint Oriented Networks. 2020. №8. P. 44459–44469.
6. Brohi A. M., Malkani Y. A., Chandio M. S. Data provenance in Wireless Sensor Networks (WSNs) // A review. In Proceedings of the 2018 International Conference on Computing, Mathematics and Engineering Technologies (iCoMET). Sukkur, Pakistan, 3–4 March 2018. P. 1–5.
7. Clustering Analysis in Wireless Sensor Networks / A. Zeb, A. K. M. M. Islam, M. Zareei [et al.] // The Ambit of Performance Metrics and Schemes Taxonomy. Int. J. Distrib. Sens. Netw. 2016. №12. P. 4979142.
8. Improving Energy Efficiency With Content-Based Adaptive and Dynamic Scheduling in WSN. / M. N. Khan, H. U. Rahman, M. A. Almaiah [et al.] // Constraint Oriented Networks. 2020. №8. P. 176495–176520.
9. Minet P. Energy Efficient Routing // Bentham Science: Sharjah, United Arab Emirates. 2009. P. 49–60.
10. Heinzelman W. B., Chandrakasan A. P., Balakrishnan H. An Application-Specific Protocol Architecture for Wireless Microsensor Networks // IEEE Trans. Wirel. Commun. 2002. №1. P. 660–670.
11. Lindsey S., Raghavendra C., Sivalingam K. M. Data gathering algorithms in sensor networks using energy metrics // IEEE Trans. Parallel Distrib. Syst. 2002. №13. P. 924–935.
12. Recursive Shortest Path Routing Algorithm with Application for Wireless Sensor Network Localization / J. Cota-Ruiz, P. Rivas-Perea, E. Sifuentes, R. A. Gonzalez-Landaeta // IEEE Sens. J. 2016. №16. P. 4631–4637.
13. On Optimal Scheduling in Duty-Cycled Industrial IoT Applications Using / M. R. Palattella, N. Accettura, L. A. Grieco [et al.] // IEEE802.15.4e TSCH. IEEE Sens. J. 2013. №13. P. 3655–3666.
14. Rachmad A. A., Daoguo Y. Online Monitoring & Controlling Industrial Arm Robot Using MQTT Protocol // In Proceedings of the 2018 IEEE International Conference on Robotics, Biomimetics, and Intelligent Computational Systems (Robionetics). Bandung, Indonesia, 8–10 August 2018. P. 12–16.