000 04010nam a22005055i 4500
001 vtls000541720
003 RU-ToGU
005 20210922082128.0
007 cr nn 008mamaa
008 160915s2014 xxu| s |||| 0|eng d
020 _a9781493919055
_9978-1-4939-1905-5
024 7 _a10.1007/978-1-4939-1905-5
_2doi
035 _ato000541720
040 _aSpringer
_cSpringer
_dRU-ToGU
050 4 _aQA75.5-76.95
072 7 _aUT
_2bicssc
072 7 _aCOM069000
_2bisacsh
072 7 _aCOM032000
_2bisacsh
082 0 4 _a005.7
_223
245 1 0 _aCloud Computing for Data-Intensive Applications
_helectronic resource
_cedited by Xiaolin Li, Judy Qiu.
260 _aNew York, NY :
_bSpringer New York :
_bImprint: Springer,
_c2014.
300 _aVIII, 427 p. 180 illus.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
505 0 _aScalable Deployment of a LIGO Physics Application on Public Clouds:Workflow Engine and Resource Provisioning Techniques -- The FutureGrid Testbed for Big Data -- Cloud Networking to Support Data Intensive Applications -- IaaS cloud benchmarking: approaches, challenges, and experience -- Adaptive Workload Partitioning and Allocation for Data Intensive Scientific Applications -- Federating Advanced CyberInfrastructures with Autonomic Capabilities -- Executing Storm Surge Ensembles on PAAS Cloud -- Migrating Scientific Workflow Management Systems from the Grid to the Cloud -- Efficient Task-Resource Matchmaking Using Self-Adaptive Combinatorial Auction -- Cross-Phase Optimization in MapReduce -- DRAW: A New Data-gRouping-AWare Data Placement Scheme for Data Intensive Applications with Interest Locality -- Maiter: An Asynchronous Graph Processing Framework for Delta-based Accumulative Iterative Computation -- GPU-Accelerated Cloud Computing Data-Intensive Applications -- Big Data Storage and Processing on Azure Clouds: Experiments at Scale and Lessons Learned -- Storage and Data Lifecycle Management in Cloud  Environments with FRIEDA -- DTaaS: Data Transfer as a Service in the Cloud -- Supporting a Social Media Observatory with Customizable Index Structures — Architecture and Performance.
520 _aThis book presents a range of cloud computing platforms for data-intensive scientific applications. It covers systems that deliver infrastructure as a service, including: HPC as a service; virtual networks as a service; scalable and reliable storage; algorithms that manage vast cloud resources and applications runtime; and programming models that enable pragmatic programming and implementation toolkits for eScience applications. Many scientific applications in clouds are also introduced, such as bioinformatics, biology, weather forecasting and social networks. Most chapters include case studies. Cloud Computing for Data-Intensive Applications targets advanced-level students and researchers studying computer science and electrical engineering. Professionals working in cloud computing, networks, databases and more will also find this book useful as a reference.
650 0 _aComputer Science.
_9155490
650 0 _aComputer Communication Networks.
_9566243
650 0 _aInformation systems.
_9303226
650 0 _aDatabase management.
_9566224
650 1 4 _aComputer Science.
_9155490
650 2 4 _aInformation Systems and Communication Service.
_9304271
650 2 4 _aComputer Communication Networks.
_9566243
650 2 4 _aInformation Systems Applications (incl. Internet).
_9299051
650 2 4 _aDatabase Management.
_9566226
700 1 _aLi, Xiaolin.
_eeditor.
_9413385
700 1 _aQiu, Judy.
_eeditor.
_9447067
710 2 _aSpringerLink (Online service)
_9143950
773 0 _tSpringer eBooks
856 4 0 _uhttp://dx.doi.org/10.1007/978-1-4939-1905-5
912 _aZDB-2-SCS
999 _c399398