LEADER 04877nam 22005655 450 001 9910299287103321 005 20201102195513.0 010 $a3-319-73876-3 024 7 $a10.1007/978-3-319-73876-5 035 $a(CKB)3840000000347748 035 $a(MiAaPQ)EBC5287942 035 $a(DE-He213)978-3-319-73876-5 035 $a(PPN)224640860 035 $a(EXLCZ)993840000000347748 100 $a20180210d2018 u| 0 101 0 $aeng 135 $aurcnu|||||||| 181 $2rdacontent 182 $2rdamedia 183 $2rdacarrier 200 10$aEconomic Models for Managing Cloud Services$b[electronic resource] /$fby Sajib Mistry, Athman Bouguettaya, Hai Dong 205 $a1st ed. 2018. 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2018. 215 $a1 online resource (141 pages) $cillustrations 311 $a3-319-73875-5 320 $aIncludes bibliographical references. 327 $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. 330 $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. . 606 $aApplication software 606 $aManagement information systems 606 $aComputer science 606 $aComputer communication systems 606 $aInformation Systems Applications (incl. Internet)$3https://scigraph.springernature.com/ontologies/product-market-codes/I18040 606 $aManagement of Computing and Information Systems$3https://scigraph.springernature.com/ontologies/product-market-codes/I24067 606 $aComputer Communication Networks$3https://scigraph.springernature.com/ontologies/product-market-codes/I13022 615 0$aApplication software. 615 0$aManagement information systems. 615 0$aComputer science. 615 0$aComputer communication systems. 615 14$aInformation Systems Applications (incl. Internet). 615 24$aManagement of Computing and Information Systems. 615 24$aComputer Communication Networks. 676 $a004.6782 700 $aMistry$b Sajib$4aut$4http://id.loc.gov/vocabulary/relators/aut$0952979 702 $aBouguettaya$b Athman$4aut$4http://id.loc.gov/vocabulary/relators/aut 702 $aDong$b Hai$4aut$4http://id.loc.gov/vocabulary/relators/aut 906 $aBOOK 912 $a9910299287103321 996 $aEconomic Models for Managing Cloud Services$92154567 997 $aUNINA