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Erschienen in:
Towards the Usage of CCN for IoT Networks Kapitel lesen Erstes Kapitel lesen

2016 | OriginalPaper | Buchkapitel

Signal Processing Techniques for Energy Efficiency, Security, and Reliability in the IoT Domain

verfasst von : Alexandros Fragkiadakis, Elias Tragos, Antonis Makrogiannakis, Stefanos Papadakis, Pavlos Charalampidis, Manolis Surligas

Erschienen in: Internet of Things (IoT) in 5G Mobile Technologies

Verlag: Springer International Publishing

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Abstract

The next generation of communication networks, known as 5G technologies, is envisioned to address several major technical challenges like increased data rates, efficient spectral use, higher capacity, etc. One of the core pillars of the 5G technologies is the Internet of Things (IoT) use-case. This employs hundreds or even thousands of smart objects serving numerous applications (e.g. environmental monitoring, smart homes, smart traffic management, etc.). Typical IoT applications become feasible through the use of large-scale Wireless Sensor Networks deployed using a number of miniature devices called as sensors or motes. In this chapter, we demonstrate how two popular signal processing techniques, namely Compressive Sensing and Matrix Completion can be used to make feasible energy efficiency, lightweight encryption, and packet loss mitigation. Furthermore, we present an IoT platform based on a Software Defined Radio that provides multiple channel support for both IEEE 802.11 and IEEE 802.15.4 standards.

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Vorheriges Kapitel Security Challenges in 5G-Based IoT Middleware Systems
Nächstes Kapitel IoT Enablers and Their Security and Privacy Issues
Fußnoten
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Metadaten
Titel
Signal Processing Techniques for Energy Efficiency, Security, and Reliability in the IoT Domain
verfasst von
Alexandros Fragkiadakis
Elias Tragos
Antonis Makrogiannakis
Stefanos Papadakis
Pavlos Charalampidis
Manolis Surligas
Copyright-Jahr
2016
Buch
Internet of Things (IoT) in 5G Mobile Technologies

Print ISBN: 978-3-319-30911-8

Electronic ISBN: 978-3-319-30913-2

Copyright-Jahr: 2016

DOI
https://doi.org/10.1007/978-3-319-30913-2_18

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