Cloud Broker and Cloudlet for Workflow Scheduling

This book blends the principles of cloud computing theory and discussion of emerging technologies in cloud broker systems, enabling users to realise the potential of an integrated broker system for scientific applications and the Internet of Things (IoT). Due to dynamic situations in user demand and...

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Main Authors: Youn, Chan-Hyun. (Author, http://id.loc.gov/vocabulary/relators/aut), Chen, Min. (http://id.loc.gov/vocabulary/relators/aut), Dazzi, Patrizio. (http://id.loc.gov/vocabulary/relators/aut)
Corporate Author: SpringerLink (Online service)
Language:English
Published: Singapore : Springer Singapore : Imprint: Springer, 2017.
Edition:1st ed. 2017.
Series:KAIST Research Series,
Subjects:
Online Access:https://doi.org/10.1007/978-981-10-5071-8
Summary:This book blends the principles of cloud computing theory and discussion of emerging technologies in cloud broker systems, enabling users to realise the potential of an integrated broker system for scientific applications and the Internet of Things (IoT). Due to dynamic situations in user demand and cloud resource status, scalability has become crucial in the execution of complex scientific applications. Therefore, data analysts and computer scientists must grasp workflow management issues in order to better understand the characteristics of cloud resources, allocate these resources more efficiently and make critical decisions intelligently. Thus, this book addresses these issues through discussion of some novel approaches and engineering issues in cloud broker systems and cloudlets for workflow scheduling. This book closes the gaps between cloud programmers and scientific applications designers, describing the fundamentals of cloud broker system technology and the state-of-the-art applications in implementation and performance evaluation. The books gives details of scheduling structures and processes, providing guidance and inspiration for users including cloud programmers, application designers and decision makers with involvement in cloud resource management.
Physical Description:IX, 212 p. 92 illus., 48 illus. in color. online resource.
ISBN:9789811050718
ISSN:2214-2541