optimized cloud resource management and scheduling

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Optimized Cloud Resource Management and Scheduling
Author :
Publisher : Morgan Kaufmann
Release Date :
ISBN 10 : 0128016450
Pages : 284 pages
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Optimized Cloud Resource Management and Scheduling identifies research directions and technologies that will facilitate efficient management and scheduling of computing resources in cloud data centers supporting scientific, industrial, business, and consumer applications. It serves as a valuable reference for systems architects, practitioners, developers, researchers and graduate level students. Explains how to optimally model and schedule computing resources in cloud computing Provides in depth quality analysis of different load-balance and energy-efficient scheduling algorithms for cloud data centers and Hadoop clusters Introduces real-world applications, including business, scientific and related case studies Discusses different cloud platforms with real test-bed and simulation tools

Optimized Cloud Resource Management and Scheduling

Optimized Cloud Resource Management and Scheduling identifies research directions and technologies that will facilitate efficient management and scheduling of computing resources in cloud data centers supporting scientific, industrial, business, and consumer applications. It serves as a valuable reference for systems architects, practitioners, developers, researchers and graduate level students. Explains how

GET BOOK!
Optimized Cloud Resource Management and Scheduling

This book identifies research directions and technologies that will facilitate efficient management and scheduling of computing resources in cloud data centers supporting scientific, industrial, business, and consumer applications. It describes how to optimally model and schedule computing resources in cloud computing and provides analysis of different load-balance and energy-efficient scheduling

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Optimized Cloud Based Scheduling

This book presents an improved design for service provisioning and allocation models that are validated through running genome sequence assembly tasks in a hybrid cloud environment. It proposes approaches for addressing scheduling and performance issues in big data analytics and showcases new algorithms for hybrid cloud scheduling. Scientific sectors such

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Resource Management in Utility and Cloud Computing

This SpringerBrief reviews the existing market-oriented strategies for economically managing resource allocation in distributed systems. It describes three new schemes that address cost-efficiency, user incentives, and allocation fairness with regard to different scheduling contexts. The first scheme, taking the Amazon EC2TM market as a case of study, investigates the

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Autonomic Computing in Cloud Resource Management in Industry 4 0

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Adaptive Resource Management and Scheduling for Cloud Computing

This book constitutes the thoroughly refereed post-conference proceedings of the First International Workshop on Adaptive Resource Management and Scheduling for Cloud Computing, ARMS-CC 2014, held in Conjunction with ACM Symposium on Principles of Distributed Computing, PODC 2014, in Paris, France, in July 2014. The 14 revised full papers (including 2 invited talks) were carefully reviewed

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Advances in Service Oriented and Cloud Computing

This volume contains the technical papers presented in the workshops, PhD Symposium and EU Projects Track which took place at the 8th European Conference on Service-Oriented and Cloud Computing, ESOCC 2020, held in Heraklion, Crete, Greece, in September 2020: 1st International Workshop on Edge Adoption and Migration, EdgeWays 2020, 16th International Workshop on

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This book constitutes the refereed proceedings of the 21th International Conference on Distributed and Computer and Communication Networks, DCCN 2018, held in Moscow, Russia, in September 2018. The 50 full papers and the 9 short papers were carefully reviewed and selected from 168 submissions. The papers cover the following topics: computer and communication networks architecture

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Job Scheduling Strategies for Parallel Processing

This book constitutes the thoroughly refereed post-conference proceedings of the 19th and 20th International Workshop on Job Scheduling Strategies for Parallel Processing, JSSPP 2015 and 2016, held respectively in Hyderabad, India, on May 26, 2015 and in Chicago, IL, USA, on May 27, 2016. The 14 revised full papers presented (7 papers in 2015 and 7 papers in 2016) were carefully

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Cloud Computing

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Intelligent Resource Scheduling with Neutrosophic Knowledge and Optimized Cache Management Using Cuckoo Search Method in Cloud Computing

The cloud environment comprised of distributed resources in a dynamic fashion, so this necessitates the need for developing optimal scheduling in cloud environment with the satisfaction of Quality of Service necessitated by the cloud consumer with the maximum profit to cloud providers. But the presence of impreciseness while scheduling cloud

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Society is now completely driven by data with many industries relying on data to conduct business or basic functions within the organization. With the efficiencies that big data bring to all institutions, data is continuously being collected and analyzed. However, data sets may be too complex for traditional data-processing, and

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With the immense amount of data that is now available online, security concerns have been an issue from the start, and have grown as new technologies are increasingly integrated in data collection, storage, and transmission. Online cyber threats, cyber terrorism, hacking, and other cybercrimes have begun to take advantage of

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