Computation and Storage in the Cloud: Understanding the Trade-Offs
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AlbakiReads Editorial Managing the cloud cost of recomputation versus retention
Managing the cloud cost of recomputation versus retention
Dong Yuan examines a central systems-design question for data-intensive scientific work: when is it more economical to preserve generated datasets, and when is it preferable to recreate them? Framed around cloud environments, the book addresses applications whose processing can be lengthy and whose outputs may reach terabyte or petabyte scale. It presents cost models and benchmarking as tools for weighing computation against storage, then considers strategies for keeping application data in the cloud. Case studies from scientific research ground the discussion in practical application contexts. The emphasis is on the economic and operational trade-offs facing both cloud users and service providers, with algorithms and theorems forming part of the proposed approach.
Good fit for readers who enjoy
- Cloud-computing practitioners working with computation- and data-intensive workloads
- Researchers and students interested in distributed systems cost modeling
- Technical readers seeking scientific-application case studies in cloud storage
Themes
Cloud computingData storage versus recomputationCost models and benchmarkingScientific datasetsDistributed systems
Based on publisher information and book metadata.
Book Overview Computation and Storage in the Cloud is the first comprehensive and systematic work investigating the issue of computation and storage tr...
Computation and Storage in the Cloud is the first comprehensive and systematic work investigating the issue of computation and storage trade-off in the cloud in order to reduce the overall application cost. Scientific applications are usually computation and data intensive, where complex computation tasks take a long time for execution and the generated datasets are often terabytes or petabytes in size. Storing valuable generated application datasets can save their regeneration cost when they are reused, not to mention the waiting time caused by regeneration. However, the large size of the scientific datasets is a big challenge for their storage. By proposing innovative concepts, theorems and algorithms, this book will help bring the cost down dramatically for both cloud users and service providers to run computation and data intensive scientific applications in the cloud.
- Covers cost models and benchmarking that explain the necessary tradeoffs for both cloud providers and users
- Describes several novel strategies for storing application datasets in the cloud
- Includes real-world case studies of scientific research applications
Book Details Format: Paperback | Pages: 128 | Language: English | Publisher: ELSEVIER | ISBN: 0124077676
FormatPaperback
Pages128
LanguageEnglish
ISBN0124077676
EAN9780124077676
PublisherELSEVIER
Publication Date2013-02-01
Edition1
AccessoriesNo Accessory
ConditionNew
Product TypeQUALITY PAPERBACK BOOKS
Weight0.4 Pounds
Length9.0 Inches
Width6.0 Inches
Height0.27 Inches
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