1.

Record Nr.

UNINA9910298553103321

Autore

Schaffner Jan

Titolo

Multi tenancy for cloud-based in-memory column databases : workload management and data placement / / Jan Schaffner

Pubbl/distr/stampa

New York, : Springer, 2014

ISBN

3-319-00497-2

Edizione

[1st ed. 2014.]

Descrizione fisica

1 online resource (140 p.)

Collana

In-memory data management research

Disciplina

005.74

Soggetti

Cloud computing

Application service providers

Lingua di pubblicazione

Inglese

Formato

Materiale a stampa

Livello bibliografico

Monografia

Note generali

Description based upon print version of record.

Nota di bibliografia

Includes bibliographical references.

Nota di contenuto

1. 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.

Sommario/riassunto

With 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.