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001 978-3-319-00497-6
003 DE-He213
005 20200420211751.0
007 cr nn 008mamaa
008 130702s2014 gw | s |||| 0|eng d
020 _a9783319004976
_9978-3-319-00497-6
024 7 _a10.1007/978-3-319-00497-6
_2doi
050 4 _aHF54.5-54.56
072 7 _aKJQ
_2bicssc
072 7 _aUF
_2bicssc
072 7 _aBUS083000
_2bisacsh
072 7 _aCOM039000
_2bisacsh
082 0 4 _a650
_223
082 0 4 _a658.05
_223
100 1 _aSchaffner, Jan.
_eauthor.
245 1 0 _aMulti Tenancy for Cloud-Based In-Memory Column Databases
_h[electronic resource] :
_bWorkload Management and Data Placement /
_cby Jan Schaffner.
264 1 _aHeidelberg :
_bSpringer International Publishing :
_bImprint: Springer,
_c2014.
300 _aXIII, 128 p.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aIn-Memory Data Management Research,
_x2196-8055
505 0 _a1. Introduction -- 2. Background and Motivation -- 3. A Model for Load Management and Response Time Prediction -- 4. The Robust Tenant Placement and Migration Problem -- 5. Algorithms for RTP -- 6. Experimental Evaluation -- 7. Related Work -- 8. Conclusions and Perspectives.
520 _aWith the proliferation of Software-as-a-Service (SaaS) offerings, it is becoming increasingly important for individual SaaS providers to operate their services at a low cost. This book investigates SaaS from the perspective of the provider and shows how operational costs can be reduced by using "multi tenancy," a technique for consolidating a large number of customers onto a small number of servers. Specifically, the book addresses multi tenancy on the database level, focusing on in-memory column databases, which are the backbone of many important new enterprise applications. For efficiently implementing multi tenancy in a farm of databases, two fundamental challenges must be addressed, (i) workload modeling and (ii) data placement. The first involves estimating the (shared) resource consumption for multi tenancy on a single in-memory database server. The second consists in assigning tenants to servers in a way that minimizes the number of required servers (and thus costs) based on the assumed workload model. This step also entails replicating tenants for performance and high availability. This book presents novel solutions to both problems.
650 0 _aBusiness.
650 0 _aInformation technology.
650 0 _aBusiness
_xData processing.
650 0 _aAlgorithms.
650 0 _aComputers.
650 0 _aDatabase management.
650 0 _aMathematical optimization.
650 1 4 _aBusiness and Management.
650 2 4 _aIT in Business.
650 2 4 _aDatabase Management.
650 2 4 _aAlgorithm Analysis and Problem Complexity.
650 2 4 _aModels and Principles.
650 2 4 _aDiscrete Optimization.
710 2 _aSpringerLink (Online service)
773 0 _tSpringer eBooks
776 0 8 _iPrinted edition:
_z9783319004969
830 0 _aIn-Memory Data Management Research,
_x2196-8055
856 4 0 _uhttp://dx.doi.org/10.1007/978-3-319-00497-6
912 _aZDB-2-SBE
942 _cEBK
999 _c51264
_d51264