Notice bibliographique
- Notice
Type(s) de contenu et mode(s) de consultation : Texte noté : électronique
Titre(s) : Cloud Networking for Big Data [Texte électronique] / by Deze Zeng, Lin Gu, Song Guo
Édition : 1st ed. 2015
Publication : Cham : Springer International Publishing, 2015
Description matérielle : 1 online resource (XIV, 102 p. 37 illus., 1 illus. in color :)
Collection : Wireless Networks
Lien à la collection : Wireless networks (Cham. Online)
Note(s) : This book introduces two basic big data processing paradigms for batch data and streaming
data. Representative programming frameworks are also presented, as well as software
defined networking (SDN) and network function virtualization (NFV) technologies as
key cloud networking technologies. The authors illustrate that SDN and NFV can be
applied to benefit the big data processing by proposing a cloud networking framework.
Based on the framework, two case studies examine how to improve the cost efficiency
of big data processing. Cloud Networking for Big Data targets professionals and researchers
working in big data, networks, wireless communicationsand information technology.
Advanced-level students studying computer science and electrical engineering will
also find this book valuable as a study guide
Autre(s) auteur(s) : Zeng, Deze. Fonction indéterminée
Gu, Lin. Fonction indéterminée
Guo, Song. Fonction indéterminée
Sujet(s) : Informatique
Réseaux d'ordinateurs
Indice(s) Dewey :
004.6 (23e éd.) = Interfaçages et communications (informatique)
Identifiants, prix et caractéristiques : ISBN 9783319247205
Identifiant de la notice : ark:/12148/cb44680710z
Notice n° :
FRBNF44680710
(notice reprise d'un réservoir extérieur)
Table des matières : Networking Evolution towards Cloud Networking ; Background Introduction ; Fundamental
Concepts ; Cloud Networking ; Cost Efficient Big Data Processing in Cloud Networking
enabled Data Centers ; Cost Minimization for Big Data Processing in Geo-Distributed
Data Centers ; A General Communication Cost Optimization Framework for Big Data Stream
Processing in Geo-distributed Data Centers ; Conclusion and Future Work.