Computing in Communication Networks : From Theory to Practice
Language: English
Published by Elsevier Inc Mai 2020, 2020
- Softcover
- New
Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH
AbeBooks seller since August 14, 2006
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Add to basketItem description from seller
Neuware - Computing in Communication Networks: From Theory to Practice provides comprehensive details and practical implementation tactics on the novel concepts and enabling technologies at the core of the paradigm shift from store and forward (dumb) to compute and forward (intelligent) in future communication networks and systems. The book explains how to create virtualized large scale testbeds using well-established open source software, such as Mininet and Docker. It shows how and where to place disruptive techniques, such as machine learning, compressed sensing, or network coding in a newly built testbed. In addition, it presents a comprehensive overview of current standardization activities. Specific chapters explore upcoming communication networks that support verticals in transportation, industry, construction, agriculture, health care and energy grids, underlying concepts, such as network slicing and mobile edge cloud, enabling technologies, such as SDN/NFV/ ICN, disruptive innovations, such as network coding, compressed sensing and machine learning, how to build a virtualized network infrastructure testbed on one's own computer, and more.…
Seller Inventory # 9780128204887
- Title
- Computing in Communication Networks : From Theory to Practice
- Author
- Patrick Seeling
- Publisher
- Elsevier Inc Mai 2020
- Publication year
- 2020
- Condition
- Neu
- Binding
- Taschenbuch
- Language
- English
- ISBN 10
- 0128204885
- ISBN 13
- 9780128204887
- Item weight
- 892 grams
- Dimensions
- 235x191x27 mm
Computing in Communication Networks: From Theory to Practice provides comprehensive details and practical implementation tactics on the novel concepts and enabling technologies at the core of the paradigm shift from store and forward (dumb) to compute and forward (intelligent) in future communication networks and systems. The book explains how to create virtualized large scale testbeds using well-established open source software, such as Mininet and Docker. It shows how and where to place disruptive techniques, such as machine learning, compressed sensing, or network coding in a newly built testbed. In addition, it presents a comprehensive overview of current standardization activities.
Specific chapters explore upcoming communication networks that support verticals in transportation, industry, construction, agriculture, health care and energy grids, underlying concepts, such as network slicing and mobile edge cloud, enabling technologies, such as SDN/NFV/ ICN, disruptive innovations, such as network coding, compressed sensing and machine learning, how to build a virtualized network infrastructure testbed on one's own computer, and more.
"Synopsis" may belong to another edition of this title.
About the Author
He received his diploma (Dipl.-Ing.) degree in electrical engineering from the University of Technology – Rheinisch-Westfälische Technische Hochschule (RWTH) – Aachen, Germany, in 1997 and his Ph.D. (Dr.-Ing.) in Electrical Engineering from the Technical University Berlin, Germany in 2002 and became Adjunct Professor at the University of Ferrara, Italy in the same year. In 2003 he joined Aalborg University as Professor
.
Fabrizio Granelli is Associate Professor at the Dept. of Information Engineering and Computer Science (DISI) – University of Trento (Italy), IEEE ComSoc Director for Educational Services (2018-19) and Chair of Joint IEEE VTS/ComSoc Italian Chapter. He is Research Associate Professor at the University of New Mexico, NM, USA.
He received the M.Sc. and Ph.D. degrees from University of Genoa, Italy, in 1997 and 2001. He was visiting professor at the State University of Campinas (Brasil) and at the University of Tokyo (Japan), and IEEE ComSoc Distinguished Lecturer in 2012-15.
He is Associate Editor in Chief of IEEE Communications Surveys and Tutorials.
Patrick Seeling is a Professor in the Department of Computer Science at Central Michigan University, USA. He received his diploma (Dipl.-Ing.) degree in Industrial Engineering and Management from the Technical University Berlin, Germany, in 2002 and his his Ph.D. in Electrical Engineering from Arizona State University (ASU), USA, in 2005. He was an Associated Faculty at ASU until 2008 and an Assistant Professor at the University of Wisconsin-Stevens Point until 2011. In 2011, he joined Central Michigan University as Assistant Professor, where he became a tenured Associate Professor in 2015 and a Full Professor in 2018.
"About the title" may belong to another edition of this title.
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