000 | 05273nam a22005895i 4500 | ||
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001 | 978-3-319-73876-5 | ||
003 | DE-He213 | ||
005 | 20210201191516.0 | ||
007 | cr nn 008mamaa | ||
008 | 180210s2018 gw | s |||| 0|eng d | ||
020 |
_a9783319738765 _9978-3-319-73876-5 |
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050 | 4 | _aQA76.76.A65 | |
072 | 7 |
_aUNH _2bicssc |
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072 | 7 |
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_aUNH _2thema |
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072 | 7 |
_aUDBD _2thema |
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082 | 0 | 4 |
_a005.7 _223 |
100 | 1 |
_aMistry, Sajib. _eauthor. _0(orcid)0000-0001-7513-3789 _1https://orcid.org/0000-0001-7513-3789 _4aut _4http://id.loc.gov/vocabulary/relators/aut |
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245 | 1 | 0 |
_aEconomic Models for Managing Cloud Services _h[electronic resource] / _cby Sajib Mistry, Athman Bouguettaya, Hai Dong. |
250 | _a1st ed. 2018. | ||
264 | 1 |
_aCham : _bSpringer International Publishing : _bImprint: Springer, _c2018. |
|
300 |
_aXIX, 141 p. 53 illus., 12 illus. in color. _bonline resource. |
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336 |
_atext _btxt _2rdacontent |
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337 |
_acomputer _bc _2rdamedia |
||
338 |
_aonline resource _bcr _2rdacarrier |
||
347 |
_atext file _bPDF _2rda |
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500 | _aAcceso multiusuario | ||
505 | 0 | _a1 Introduction -- 2 Cloud Service Composition: The State of the Art -- 3 Long-term IaaS Composition for Deterministic Requests -- 4 Long-term IaaS Composition for Stochastic Requests -- 5 Long-term Qualitative IaaS Composition -- 6 Service Providers' Long-term QoS Prediction Model -- 7 Conclusion. | |
520 | _aThe authors introduce both the quantitative and qualitative economic models as optimization tools for the selection of long-term cloud service requests. The economic models fit almost intuitively in the way business is usually done and maximize the profit of a cloud provider for a long-term period. The authors propose a new multivariate Hidden Markov and Autoregressive Integrated Moving Average (HMM-ARIMA) model to predict various patterns of runtime resource utilization. A heuristic-based Integer Linear Programming (ILP) optimization approach is developed to maximize the runtime resource utilization. It deploys a Dynamic Bayesian Network (DBN) to model the dynamic pricing and long-term operating cost. A new Hybrid Adaptive Genetic Algorithm (HAGA) is proposed that optimizes a non-linear profit function periodically to address the stochastic arrival of requests. Next, the authors explore the Temporal Conditional Preference Network (TempCP-Net) as the qualitative economic model to represent the high-level IaaS business strategies. The temporal qualitative preferences are indexed in a multidimensional k-d tree to efficiently compute the preference ranking at runtime. A three-dimensional Q-learning approach is developed to find an optimal qualitative composition using statistical analysis on historical request patterns. Finally, the authors propose a new multivariate approach to predict future Quality of Service (QoS) performances of peer service providers to efficiently configure a TempCP-Net. It discusses the experimental results and evaluates the efficiency of the proposed composition framework using Google Cluster data, real-world QoS data, and synthetic data. It also explores the significance of the proposed approach in creating an economically viable and stable cloud market. This book can be utilized as a useful reference to anyone who is interested in theory, practice, and application of economic models in cloud computing. This book will be an invaluable guide for small and medium entrepreneurs who have invested or plan to invest in cloud infrastructures and services. Overall, this book is suitable for a wide audience that includes students, researchers, and practitioners studying or working in service-oriented computing and cloud computing. . | ||
541 |
_fUABC ; _cTemporal ; _d01/01/2021-12/31/2023. |
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650 | 0 | _aApplication software. | |
650 | 0 | _aManagement information systems. | |
650 | 0 | _aComputer science. | |
650 | 0 | _aComputer communication systems. | |
650 | 1 | 4 |
_aInformation Systems Applications (incl. Internet). _0https://scigraph.springernature.com/ontologies/product-market-codes/I18040 |
650 | 2 | 4 |
_aManagement of Computing and Information Systems. _0https://scigraph.springernature.com/ontologies/product-market-codes/I24067 |
650 | 2 | 4 |
_aComputer Communication Networks. _0https://scigraph.springernature.com/ontologies/product-market-codes/I13022 |
700 | 1 |
_aBouguettaya, Athman. _eauthor. _0(orcid)0000-0003-1254-8092 _1https://orcid.org/0000-0003-1254-8092 _4aut _4http://id.loc.gov/vocabulary/relators/aut |
|
700 | 1 |
_aDong, Hai. _eauthor. _0(orcid)0000-0002-7033-5688 _1https://orcid.org/0000-0002-7033-5688 _4aut _4http://id.loc.gov/vocabulary/relators/aut |
|
710 | 2 | _aSpringerLink (Online service) | |
773 | 0 | _tSpringer Nature eBook | |
776 | 0 | 8 |
_iPrinted edition: _z9783319738758 |
776 | 0 | 8 |
_iPrinted edition: _z9783319738772 |
776 | 0 | 8 |
_iPrinted edition: _z9783319892603 |
856 | 4 | 0 |
_zLibro electrónico _uhttp://148.231.10.114:2048/login?url=https://doi.org/10.1007/978-3-319-73876-5 |
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912 | _aZDB-2-SXCS | ||
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