Title :
An Elastic OLAP Cloud Platform
Author :
Brezany, Peter ; Zhang, Yan ; Janciak, Ivan ; Chen, Peng ; Ye, Sicen
Author_Institution :
Fac. of Comput. Sci., Univ. of Vienna, Vienna, Austria
Abstract :
A typical cloud platform provides capability of scalability, elasticity and fault tolerance. Moreover, it is designed to deal with high volumes of data on nearly unlimited number of machines. On-Line Analytical Processing (OLAP), a kernel part of modern decision support systems, allows interactive analysis of multidimensional data of varied granularity. A combination of the Cloud Computing and OLAP technologies brings challenges in providing OLAP analysis services in distributed environments. This paper presents an overview of our on-going research on Elastic OLAP Cloud Platform. The design issues and implementation details are discussed, including research challenges, architecture, index and dynamic extension mechanisms, OLAP Modeling Markup Language, and related services. The experiment and performance results demonstrate the feasibility and effectiveness of the developed platform.
Keywords :
cloud computing; data analysis; data mining; decision support systems; software fault tolerance; OLAP modeling markup language; cloud computing; decision support systems; elastic OLAP cloud platform; elasticity; fault tolerance; interactive multidimensional data analysis; kernel part; online analytical processing; scalability; Arrays; Data models; Distributed databases; Indexes; Position measurement; Servers; Cloud service; distributed OLAP; virtualization;
Conference_Titel :
Dependable, Autonomic and Secure Computing (DASC), 2011 IEEE Ninth International Conference on
Conference_Location :
Sydney, NSW
Print_ISBN :
978-1-4673-0006-3
DOI :
10.1109/DASC.2011.76
