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Cloud Computing for Optimization: Foundations, Applications, and Challenges

This book discusses harnessing the real power of cloud computing in optimization problems, presenting state-of-the-art computing paradigms, advances in applications, and challenges concerning both the theories and applications of cloud computing in optimization with a focus on diverse fields like th...

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Bibliographic Details
Corporate Author: SpringerLink (Online service)
Other Authors: Mishra, Bhabani Shankar Prasad (Editor), Das, Himansu (Editor), Dehuri, Satchidananda (Editor), Jagadev, Alok Kumar (Editor)
Format: e-Book
Language:English
Published: Cham : Springer International Publishing : 2018.
Imprint: Springer,
Edition:1st ed. 2018.
Series:Studies in Big Data, 39
Subjects:
Online Access:Full-text access
Description
Summary:This book discusses harnessing the real power of cloud computing in optimization problems, presenting state-of-the-art computing paradigms, advances in applications, and challenges concerning both the theories and applications of cloud computing in optimization with a focus on diverse fields like the Internet of Things, fog-assisted cloud computing, and big data. In real life, many problems - ranging from social science to engineering sciences - can be identified as complex optimization problems. Very often these are intractable, and as a result researchers from industry as well as the academic community are concentrating their efforts on developing methods of addressing them. Further, the cloud computing paradigm plays a vital role in many areas of interest, like resource allocation, scheduling, energy management, virtualization, and security, and these areas are intertwined with many optimization problems. Using illustrations and figures, this book offers students and researchers a clear overview of the concepts and practices of cloud computing and its use in numerous complex optimization problems.
Physical Description:XIV, 463 p. 144 illus., 112 illus. in color. online resource.
ISBN:9783319736761
ISSN:2197-6511 ;
DOI:10.1007/978-3-319-73676-1