LEADER 05380nam 2200649 450 001 9910460223003321 005 20200520144314.0 010 $a0-12-801645-0 035 $a(CKB)3710000000264435 035 $a(EBL)1820203 035 $a(SSID)ssj0001413071 035 $a(PQKBManifestationID)11723786 035 $a(PQKBTitleCode)TC0001413071 035 $a(PQKBWorkID)11723786 035 $a(PQKB)11723786 035 $a(MiAaPQ)EBC1820203 035 $a(CaSebORM)9780128014769 035 $a(Au-PeEL)EBL1820203 035 $a(CaPaEBR)ebr10958316 035 $a(CaONFJC)MIL657040 035 $a(OCoLC)896729213 035 $a(EXLCZ)993710000000264435 100 $a20141106h20152015 uy 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 10$aOptimized cloud resource management and scheduling $etheory and practice /$fWenhong Tian, Yong Zhao 205 $a1st edition 210 1$aWaltham, Massachusetts :$cMorgan Kaufmann,$d2015. 210 4$dİ2015 215 $a1 online resource (285 p.) 300 $aDescription based upon print version of record. 311 $a1-322-25760-4 311 $a0-12-801476-8 320 $aIncludes bibliographical references at the end of each chapters. 327 $aFront Cover; Optimized Cloud Resource Management and Scheduling; Copyright Page; Contents; Foreword; Preface; About the Authors; Acknowledgments; 1 An Introduction to Cloud Computing; Main Contents of this Chapter; 1.1 The background of Cloud computing; 1.2 Cloud computing is an integration of other advanced technologies; 1.2.1 Parallel computing; 1.2.2 Grid computing; 1.2.3 Utility computing; 1.2.4 Ubiquitous computing; 1.2.5 Software as a service; 1.2.6 Virtualization technology; 1.3 The driving forces of Cloud computing; 1.4 The development status and trends of Cloud computing 327 $a1.5 The classification of Cloud computing applications1.5.1 Classification by service type; 1.5.2 Classification by deployment method; 1.6 The different roles in the Cloud computing industry chain; 1.7 The main features and technical challenges of Cloud computing; 1.7.1 The main features of Cloud computing; 1.7.2 Challenging issues; Summary; References; 2 Big Data Technologies and Cloud Computing; Main Contents of this Chapter; 2.1 The background and definition of big data; 2.2 Big data problems; 2.2.1 The problem of speed; 2.2.2 The type and architecture problem 327 $a2.2.3 Volume and flexibility problems2.2.4 The cost problem; 2.2.5 The value mining problem; 2.2.6 The security and privacy problem; 2.2.7 Interoperability and data sharing issues; 2.3 The dialectical relationship between Cloud computing and big data; 2.4 Big data technologies; 2.4.1 Infrastructure support; 2.4.2 Data acquisition; 2.4.3 Data storage; 2.4.4 Data computing; 2.4.4.1 Offline batch computing; 2.4.4.2 Real-time interactive computing; 2.4.4.3 Streaming computing; 2.4.5 Data presentation and interaction; 2.4.6 Related work; Summary; Acknowledgments; References 327 $a3 Resource Modeling and Definitions for Cloud Data CentersMain Contents of this Chapter; 3.1 Resource models in Cloud data centers; 3.2 Data center resources; 3.3 Categories of Cloud data center resources; 3.3.1 Properties and operations of various resources; 3.3.1.1 Physical servers (PMs); 3.3.1.1.1 The main properties of a physical server; 3.3.1.1.2 Physical server states; 3.3.1.1.3 Main operations of a physical server; 3.3.1.1.4 Server operation error; 3.3.1.2 Physical server cluster; 3.3.1.2.1 Main properties of a physical server cluster; 3.3.1.2.2 States of a physical server cluster 327 $a3.3.1.2.3 Operations of a physical server cluster3.3.1.2.4 Physical server errors; 3.3.1.3 Virtual machines; 3.3.1.3.1 Properties of VMs; 3.3.1.3.2 Operations of VMs; 3.3.1.3.3 States of VMs; 3.3.1.3.4 Typical configurations of VMs; 3.3.1.4 Virtual clusters; 3.3.1.4.1 Main properties of a virtual cluster; 3.3.1.4.2 States of a virtual cluster; 3.3.1.4.3 Operations of a virtual cluster; 3.3.1.4.4 Operational errors on VMs; 3.3.1.5 Schedule domains; 3.3.1.5.1 Properties of schedule domains; 3.3.1.5.2 Operations of schedule domains; 3.3.1.5.3 States of schedule domains; 3.3.1.6 Storage 327 $a3.3.1.6.1 Properties of shared storage 330 $aOptimized 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 computingProvides in depth quality analysis of different load-balance and energy-efficient scheduling algorithms for cloud dat 606 $aCloud computing$xManagement 608 $aElectronic books. 615 0$aCloud computing$xManagement. 676 $a004.6782 700 $aTian$b Wenhong$0966167 702 $aZhao$b Yong 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910460223003321 996 $aOptimized cloud resource management and scheduling$92192497 997 $aUNINA