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010   $a3-319-00497-2
024 7 $a10.1007/978-3-319-00497-6
035   $a(CKB)2670000000403458
035   $a(EBL)1317762
035   $a(OCoLC)854976184
035   $a(SSID)ssj0000962957
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035   $a(PQKBTitleCode)TC0000962957
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035   $a(MiAaPQ)EBC1317762
035   $a(DE-He213)978-3-319-00497-6
035   $a(PPN)172422442
035   $a(EXLCZ)992670000000403458
100   $a20130606d2014      uy         0
101 0 $aeng
135   $aur|n|---|||||
181   $ctxt
182   $cc
183   $acr
200 10$aMulti tenancy for cloud-based in-memory column databases $eworkload management and data placement /$fJan Schaffner
205   $a1st ed. 2014.
210   $aNew York $cSpringer$d2014
215   $a1 online resource (140 p.)
225 0 $aIn-memory data management research
300   $aDescription based upon print version of record.
311   $a3-319-03344-1 
311   $a3-319-00496-4 
320   $aIncludes bibliographical references.
327   $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.
330   $aWith the proliferation of Software-as-a-Service (SaaS) offerings, it is becoming increasingly important for individual SaaS providers to operate their services at a low cost. This book investigates SaaS from the perspective of the provider and shows how operational costs can be reduced by using ?multi tenancy,? a technique for consolidating a large number of customers onto a small number of servers. Specifically, the book addresses multi tenancy on the database level, focusing on in-memory column databases, which are the backbone of many important new enterprise applications. For efficiently implementing multi tenancy in a farm of databases, two fundamental challenges must be addressed, (i) workload modeling and (ii) data placement. The first involves estimating the (shared) resource consumption for multi tenancy on a single in-memory database server. The second consists in assigning tenants to servers in a way that minimizes the number of required servers (and thus costs) based on the assumed workload model. This step also entails replicating tenants for performance and high availability. This book presents novel solutions to both problems.
410  0$aIn-Memory Data Management Research,$x2196-8055
606   $aCloud computing
606   $aApplication service providers
615  0$aCloud computing.
615  0$aApplication service providers.
676   $a005.74
700   $aSchaffner$b Jan$01060124
801  0$bMiAaPQ
801  1$bMiAaPQ
801  2$bMiAaPQ
906   $aBOOK
912   $a9910298553103321
996   $aMulti Tenancy for Cloud-Based In-Memory Column Databases$92511302
997   $aUNINA