Abstract
The escalating rate of deployments of real-life applications of wireless sensor networks (WSNs) has been observed over the years. Research has identified these WSNs as networks that operate with more limited energy compared to other wireless networks. Power consumption is the Achilles’ heel of the network lifetime in these networks. Most of the power is lost during the transmission of information from a source to the destination. Various approaches that aim to minimize power loss to extend the network lifetime have been proposed. Communication between sensor networks cannot be achieved physically through sensor nodes, and, therefore, there is a need for an Internet-based network (Network to Networks communications). In this chapter, we emphasized on the “Green” IoT technologies that make it environmentally friendly by focusing on optimization of data centers through techniques of sharing infrastructure, which leads to increased energy efficiency and lower cost of operation. The inexpensive, low powered sensors will expand the application of IoT to even smaller objects in any kind of environment at affordable prices. It is also anticipated that combining Energy Harvesting, Communications Techniques, and Data Compression will yield high results that will help to improve the network lifetime of Internet of Things Sensor Networks. Since these networks are suitable for large-scale deployments, large quantities of data are handled during transmission from source to sink. This also includes data that is irrelevant and may add to the energy that is wasted during the transmission of data that eventually results in reducing the network lifetime. The need for a robust and energy-efficient technique to minimize data before transmission and transmit the reduced data along the optimal transmission paths motivated this book.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
J.G. Kolo, S.A. Shanmugam, D.W.G. Lim, L.M. Ang, Fast and efficient lossless adaptive compression scheme for wireless sensor networks. Comput. Electr. Eng. 41(C), 275–287 (2015). https://doi.org/10.1016/j.compeleceng.2014.06.008
J.G. Kolo, S.A. Shanmugam, D.W.G. Lim, L.M. Ang, K.P. Seng, An adaptive lossless data compression scheme for wireless sensor networks. J. Sen. 2012 (2012). https://doi.org/10.1155/2012/539638
J. Uthayakumar, T. Vengattaraman, P. Dhavachelvan, A new lossless neighborhood indexing sequence (NIS) algorithm for data compression in wireless sensor networks. Ad Hoc Netw. 83, 149–157 (2019). https://doi.org/10.1016/j.adhoc.2018.09.009
A. Solanki, A. Nayyar, Green Internet of Things (G-IoT): ICT technologies, principles, applications, projects, and challenges. Comput. Sci., 379–405 (2019). https://doi.org/10.4018/978-1-5225-7432-3.ch021
K.K. Patel, S.M. Patel, Internet of Things-IoT: Definitions, characteristics, architecture, enabling technologies, application & future challenges. Int. J. Eng. Sci. Comput. 6(5), 6122–6123 (2016). https://doi.org/10.4010/2016.1482
M.T. Lazarescu, Wireless sensor networks for the Internet of Things: Barriers and synergies, in Components and Services for IoT Platforms, (2017). https://doi.org/10.1007/978-3-319-42304-3_9
L.K. Ketshabetswe, A.M. Zungeru, M. Mangwala, J.M. Chuma, B. Sigweni, Communication protocols for wireless sensor networks: A survey and comparison. Heliyon 5(5), e01591 (2019). https://doi.org/10.1016/j.heliyon.2019.e01591
T. Nottingham, N.E. User, School of electrical and electronic engineering energy-efficient routing algorithms based on swarm intelligence for wireless sensor networks, Adamu Murtala Zungeru, B. Eng., M.Sc. Thesis submitted to the University of Nottingham for the degree of Doc, (2013).
F. Al-Turjman, A. Kamal, M.H. Rehmani, A. Radwan, A.-S. Pathan, The Green Internet of Things (G-IoT). Hindawi Wirel. Commun. Mobile Comput. 2019, 1–2 (2019). https://doi.org/10.1155/2019/6059343
S.H. Alsamhi, O. Ma, S. Ansari and Q. Meng, Greening Internet of Things for smart everythings with a green environment life: A survey and future prospects. 1–3 (2018). [Online] Available: https://arxiv.org/ftp/arxiv/papers/1805/1805.00844.pdf
R.S. Lakshmi, RF energy harvesting for wireless devices. Int. J. Eng. Res. 11(4), 39–52 (2015). [Online]. Available: www.ijerd.com.
International Electrotechnical Commission, Internet of Things: Wireless sensor networks. 20–21 (2014). [Online] Available: https://www.ipeea.org.
S.O. Olatinwo, T.H. Joubert, Energy efficient solutions in wireless sensor systems for water quality monitoring: A review. IEEE Sens. J. 19(5), 1596–1625 (2019). https://doi.org/10.1109/JSEN.2018.2882424
K.S. Adu-Manu, N. Adam, C. Tapparello, H. Ayatollahi, W. Heinzelman, Energy-harvesting wireless sensor networks. ACM Trans. Sens. Netw. 14(2), 2–3 (2018). https://doi.org/10.1145/3183338
N. Shabbir, S.R. Hassan, Routing protocols for wireless sensor networks (WSNs). Wirel. Sens. Netw. Insights Innov. (2017). https://doi.org/10.5772/intechopen.70208
T.A. Welch, Welch_1984_Technique_for.Pdf. IEEE Comp. 17(6), 8–19 (1984)
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
Copyright information
© 2020 The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG
About this chapter
Cite this chapter
Zungeru, A.M., Ketshabetswe, L.K., Mtengi, B., Lebekwe, C.K., Chuma, J.M. (2020). Introduction to Green Internet of Things Sensor Networks. In: Green Internet of Things Sensor Networks. Springer, Cham. https://doi.org/10.1007/978-3-030-54983-1_1
Download citation
DOI: https://doi.org/10.1007/978-3-030-54983-1_1
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-54982-4
Online ISBN: 978-3-030-54983-1
eBook Packages: Computer ScienceComputer Science (R0)