Special issue on recent advancements in machine learning algorithms for internet of things

Special issue on recent advancements in machine learning algorithms for internet of things Des Autom Embed Syst (2018) 22:199–200 https://doi.org/10.1007/s10617-018-9213-4 Special issue on recent advancements in machine learning algorithms for internet of things 1 2 Gunasekaran Manogaran · Naveen Chilamkurti · Ching-Hsien Hsu Published online: 5 June 2018 © Springer Science+Business Media, LLC, part of Springer Nature 2018 In recent years, wireless sensor networks are continuously generating a massive amount of data. Processing this huge amount of data is not possible by traditional tools and technologies. Hence, there is a need for scalable machine learning algorithms to process such massive amount of data. In recent years, scalable machine learning algorithms are developed to process the massive IoT data. This special issue focused on innovations in scalable machine learning algorithms and embedded system development. The first paper, entitled QOS Distributed Routing Protocol for Mobile Ad-Hoc Wireless Networks Using Intelligent Packet Carrying Systems, by Murugeswari and Rathi, proposes an intelligent packet carrying algorithm; it provides a tracking mechanism that tracks nodes in rural places. The effectiveness and reliability has been calculated and the results are obtained using OPNET simulator. The second paper, entitled TEE based Session Key Establishment Protocol for Secure Infotainment Systems, by Sungbum Lee and Jong-Hyouk Lee, proposes a session key estab- http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Design Automation for Embedded Systems Springer Journals

Special issue on recent advancements in machine learning algorithms for internet of things

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Publisher
Springer Journals
Copyright
Copyright © 2018 by Springer Science+Business Media, LLC, part of Springer Nature
Subject
Engineering; Circuits and Systems; Computer-Aided Engineering (CAD, CAE) and Design; Special Purpose and Application-Based Systems
ISSN
0929-5585
eISSN
1572-8080
D.O.I.
10.1007/s10617-018-9213-4
Publisher site
See Article on Publisher Site

Abstract

Des Autom Embed Syst (2018) 22:199–200 https://doi.org/10.1007/s10617-018-9213-4 Special issue on recent advancements in machine learning algorithms for internet of things 1 2 Gunasekaran Manogaran · Naveen Chilamkurti · Ching-Hsien Hsu Published online: 5 June 2018 © Springer Science+Business Media, LLC, part of Springer Nature 2018 In recent years, wireless sensor networks are continuously generating a massive amount of data. Processing this huge amount of data is not possible by traditional tools and technologies. Hence, there is a need for scalable machine learning algorithms to process such massive amount of data. In recent years, scalable machine learning algorithms are developed to process the massive IoT data. This special issue focused on innovations in scalable machine learning algorithms and embedded system development. The first paper, entitled QOS Distributed Routing Protocol for Mobile Ad-Hoc Wireless Networks Using Intelligent Packet Carrying Systems, by Murugeswari and Rathi, proposes an intelligent packet carrying algorithm; it provides a tracking mechanism that tracks nodes in rural places. The effectiveness and reliability has been calculated and the results are obtained using OPNET simulator. The second paper, entitled TEE based Session Key Establishment Protocol for Secure Infotainment Systems, by Sungbum Lee and Jong-Hyouk Lee, proposes a session key estab-

Journal

Design Automation for Embedded SystemsSpringer Journals

Published: Jun 5, 2018

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