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Erschienen in:
Big Data Platforms for the Internet of Things Kapitel lesen Erstes Kapitel lesen

2014 | OriginalPaper | Buchkapitel

Adaptive Pipelined Neural Network Structure in Self-aware Internet of Things

verfasst von : Dhiya AI-Jumeily, Mohamad Al-Zawi, Abir Jaafar Hussain, Ciprian Dobre

Erschienen in: Big Data and Internet of Things: A Roadmap for Smart Environments

Verlag: Springer International Publishing

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Abstract

Self-Managing systems are a significant feature in Autonomic Computing which is required for system reliability and performance in a changing environment. The work described in this book chapter is concerned with self-healing systems; systems that can detect and analyse issues with their behavior and performance, and fixe or reconfigure as appropriate. These processes should occur in real-time to restore the desired functionality as soon as possible. The system should ideally maintain functionality during the healing process which occurs at runtime. Adaptive neural networks are proposed as a solution to some of these challenges; monitoring the system and environment, mapping a suitable solution and adapting the system accordingly. A novel application of a modified Pipelined Recurrent Neural Network is proposed in this chapter with experiments aimed to assess its applicability to online.

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Vorheriges Kapitel On RFID False Authentications
Nächstes Kapitel Spatial Dimensions of Big Data: Application of Geographical Concepts and Spatial Technology to the Internet of Things
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Metadaten
Titel
Adaptive Pipelined Neural Network Structure in Self-aware Internet of Things
verfasst von
Dhiya AI-Jumeily
Mohamad Al-Zawi
Abir Jaafar Hussain
Ciprian Dobre
Copyright-Jahr
2014
Buch
Big Data and Internet of Things: A Roadmap for Smart Environments

Print ISBN: 978-3-319-05028-7

Electronic ISBN: 978-3-319-05029-4

Copyright-Jahr: 2014

DOI
https://doi.org/10.1007/978-3-319-05029-4_5

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