Network Innovation through OpenFlow and SDN
Principles and Design
Software-defined networking (SDN) technologies powered by the OpenFlow protocol provide viable options to address the bandwidth needs of next-generation computer networks. And, since many large corporations already produce network devices that support the OpenFlow standard, there are opportunities for those who can manage complex and large-scale networks using these technologies. Network Innovation through OpenFlow and SDN: Principles and Design explains how you can use SDN and OpenFlow to build networks that are easy to design, less expensive to build and operate, and more agile and customizable. Among the first books to systematically addr…
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Produktdetails
- ISBN: 978-1-4665-7209-6
- EAN: 9781466572096
- Produktnummer: 15639847
- Verlag: Taylor & Francis Inc
- Sprache: Englisch
- Erscheinungsjahr: 2014
- Seitenangabe: 520 S.
- Masse: H24.0 cm x B16.0 cm x D3.2 cm 888 g
- Abbildungen: 12; 25 Tables, black and white; 181 Illustrations, black and white
- Gewicht: 888
- Sonstiges: Tertiary Education (US: College)
Über den Autor
Dr. Fei Hu is an associate professor in the Department of Electrical and Computer Engineering at the University of Alabama (main campus), Tuscaloosa, Alabama. He obtained his PhD at Tongji University (Shanghai, People's Republic of China) in the field of signal processing (in 1999) and at Clarkson University (New York) in the field of electrical and computer engineering (in 2002). He has published more than 150 journal/conference articles and book chapters.Dr. Hu's research has been supported by the U.S. National Science Foundation (NSF), Department of Defense (DoD), Cisco, Sprint, and other sources. His research expertise can be summarized as 3S: Security, Signals, Sensors. (1) Security: This is about how to overcome different cyber attacks in a complex wireless or wired network. Recently, he focused on cyber-physical system security and medical security issues. (2) Signals: This mainly refers to intelligent signal processing, that is, using machine learning algorithms to process sensing signals in a smart way to extract patterns (i.e., achieve pattern recognition). (3) Sensors: This includes microsensor design and wireless sensor networking issues.
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