Resource Management And Efficiency In Cloud Computing Environments
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Resource Management And Efficiency In Cloud Computing Environments
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Author : Turuk, Ashok Kumar
language : en
Publisher: IGI Global
Release Date : 2016-11-08
Resource Management And Efficiency In Cloud Computing Environments written by Turuk, Ashok Kumar and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-11-08 with Computers categories.
Today’s advancements in technology have brought about a new era of speed and simplicity for consumers and businesses. Due to these new benefits, the possibilities of universal connectivity, storage and computation are made tangible, thus leading the way to new Internet-of Things solutions. Resource Management and Efficiency in Cloud Computing Environments is an authoritative reference source for the latest scholarly research on the emerging trends of cloud computing and reveals the benefits cloud paths provide to consumers. Featuring coverage across a range of relevant perspectives and topics, such as big data, cloud security, and utility computing, this publication is an essential source for researchers, students and professionals seeking current research on the organization and productivity of cloud computing environments.
Optimized Cloud Resource Management And Scheduling
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Author : Wenhong Dr. Tian
language : en
Publisher: Morgan Kaufmann
Release Date : 2014-10-15
Optimized Cloud Resource Management And Scheduling written by Wenhong Dr. Tian and has been published by Morgan Kaufmann this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-10-15 with Computers categories.
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
Resource Management Of Mobile Cloud Computing Networks And Environments
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Author : Mastorakis, George
language : en
Publisher: IGI Global
Release Date : 2015-03-31
Resource Management Of Mobile Cloud Computing Networks And Environments written by Mastorakis, George and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-03-31 with Computers categories.
As more and more of our data is stored remotely, accessing that data wherever and whenever it is needed is a critical concern. More concerning is managing the databanks and storage space necessary to enable cloud systems. Resource Management of Mobile Cloud Computing Networks and Environments reports on the latest advances in the development of computationally intensive and cloud-based applications. Covering a wide range of problems, solutions, and perspectives, this book is a scholarly resource for specialists and end-users alike making use of the latest cloud technologies.
Adaptive Resource Management And Scheduling For Cloud Computing
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Author : Florin Pop
language : en
Publisher: Springer
Release Date : 2014-11-25
Adaptive Resource Management And Scheduling For Cloud Computing written by Florin Pop and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-11-25 with Computers categories.
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 and selected from 29 submissions and cover topics such as scheduling methods and algorithms, services and applications, fundamental models for resource management in the cloud.
Operationalizing Multi Cloud Environments
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Author : Rajganesh Nagarajan
language : en
Publisher: Springer Nature
Release Date : 2021-09-17
Operationalizing Multi Cloud Environments written by Rajganesh Nagarajan and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-09-17 with Technology & Engineering categories.
This book discusses various aspects of the multi-cloud paradigm. The initial portion of the book focuses on the motivations for the industry to embrace a multi-cloud option and the distinct business, technology, and user cases of multi-cloud implementations. The middle part of the book explains the challenges of setting up and sustaining multi-cloud environments. The latter portion focuses on the next-generation technologies and tools along with multi-cloud platforms, processes, patterns, and practices. The final segment of the book is dedicated for cloud brokerage systems. The various traits and tenets of cloud brokerage services especially for accomplishing cloud intermediation, integration, orchestration, governance, security, management, configuration, etc. are explained in detail. The book also clearly articulates how to have intelligent brokers.
Computational Intelligence For Green Cloud Computing And Digital Waste Management
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Author : Kumar, K. Dinesh
language : en
Publisher: IGI Global
Release Date : 2024-02-27
Computational Intelligence For Green Cloud Computing And Digital Waste Management written by Kumar, K. Dinesh and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-02-27 with Computers categories.
In the digital age, the relentless growth of data centers and cloud computing has given rise to a pressing dilemma. The power consumption of these facilities is spiraling out of control, emitting massive amounts of carbon dioxide, and contributing to the ever-increasing threat of global warming. Studies show that data centers alone are responsible for nearly eighty million metric tons of CO2 emissions worldwide, and this figure is poised to skyrocket to a staggering 8000 TWh by 2030 unless we revolutionize our approach to computing resource management. The root of this problem lies in inefficient resource allocation within cloud environments, as service providers often over-provision computing resources to avoid Service Level Agreement (SLA) violations, leading to both underutilization of resources and a significant increase in energy consumption. Computational Intelligence for Green Cloud Computing and Digital Waste Management stands as a beacon of hope in the face of the environmental and technological challenges we face. It introduces the concept of green computing, dedicated to creating an eco-friendly computing environment. The book explores innovative, intelligent resource management methods that can significantly reduce the power consumption of data centers. From machine learning and deep learning solutions to green virtualization technologies, this comprehensive guide explores innovative approaches to address the pressing challenges of green computing. Whether you are an educator teaching about green computing, an environmentalist seeking sustainability solutions, an industry professional navigating the digital landscape, a resolute researcher, or simply someone intrigued by the intersection of technology and sustainability, this book offers an indispensable resource.
Resource Management In Utility And Cloud Computing
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Author : Han Zhao
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-10-17
Resource Management In Utility And Cloud Computing written by Han Zhao and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-10-17 with Computers categories.
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 optimal resource rental planning models based on linear integer programming and stochastic optimization techniques. This model is useful to explore the interaction between the cloud infrastructure provider and the cloud resource customers. The second scheme targets a free-trade resource market, studying the interactions amongst multiple rational resource traders. Leveraging an optimization framework from AI, this scheme examines the spontaneous exchange of resources among multiple resource owners. Finally, the third scheme describes an experimental market-oriented resource sharing platform inspired by eBay's transaction model. The study presented in this book sheds light on economic models and their implication to the utility-oriented scheduling problems.
Resource Management Of Mobile Cloud Computing Networks And Environments
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Author :
language : en
Publisher:
Release Date : 2015
Resource Management Of Mobile Cloud Computing Networks And Environments written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015 with Cloud computing categories.
"This book reports on the latest advances in the development of computationally intensive and cloud-based applications, covering a wide range of problems, solutions, and perspectives"--
Resource Management In Distributed Systems
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Author : Anwesha Mukherjee
language : en
Publisher: Springer Nature
Release Date :
Resource Management In Distributed Systems written by Anwesha Mukherjee and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on with categories.
Virtualized Cloud Data Center Networks Issues In Resource Management
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Author : Linjiun Tsai
language : en
Publisher: Springer
Release Date : 2016-04-19
Virtualized Cloud Data Center Networks Issues In Resource Management written by Linjiun Tsai and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-04-19 with Technology & Engineering categories.
This book discusses the characteristics of virtualized cloud networking, identifies the requirements of cloud network management, and illustrates the challenges in deploying virtual clusters in multi-tenant cloud data centers. The book also introduces network partitioning techniques to provide contention-free allocation, topology-invariant reallocation, and highly efficient resource utilization, based on the Fat-tree network structure. Managing cloud data center resources without considering resource contentions among different cloud services and dynamic resource demands adversely affects the performance of cloud services and reduces the resource utilization of cloud data centers. These challenges are mainly due to strict cluster topology requirements, resource contentions between uncooperative cloud services, and spatial/temporal data center resource fragmentation. Cloud data center network resource allocation/reallocation which cope well with such challenges will allow cloud services to be provisioned with predictable network performance, mitigate service performance degradation and even guarantee service level agreements. Virtualized Cloud Data Center Networks: Issues in Resource Management tackles the challenges of managing cloud data center networks and introduces techniques to efficiently deploy large-scale distributed computing applications that require predictable performance in multi-tenant cloud data centers.