Abstract
Cloud computing has emerged as an extremely successful paradigm for deploying web applications. Scalability, elasticity, pay-per-use pricing, and economies of scale from large scale operations are the major reasons for the successful and widespread adoption of cloud infrastructures. Since a majority of cloud applications are data driven, database management systems (DBMSs) powering these applications form a critical component in the cloud software stack. In this article, we present an overview of our work on instilling these above mentioned "cloud features" in a database system designed to support a variety of applications deployed in the cloud: designing scalable database management architectures using the concepts of data fission and data fusion, enabling lightweight elasticity using low cost live database migration, and designing intelligent and autonomic controllers for system management without human intervention.
| Original language | English |
|---|---|
| Title of host publication | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
| Pages | 2-15 |
| Number of pages | 14 |
| Volume | 6587 LNCS |
| Edition | PART 1 |
| DOIs | |
| Publication status | Published - 28 Apr 2011 |
| Externally published | Yes |
| Event | 16th International Conference on Database Systems for Advanced Applications, DASFAA 2011 - Hong Kong, China Duration: 22 Apr 2011 → 25 Apr 2011 |
Publication series
| Name | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
|---|---|
| Number | PART 1 |
| Volume | 6587 LNCS |
| ISSN (Print) | 03029743 |
| ISSN (Electronic) | 16113349 |
Other
| Other | 16th International Conference on Database Systems for Advanced Applications, DASFAA 2011 |
|---|---|
| Country | China |
| City | Hong Kong |
| Period | 22/4/11 → 25/4/11 |
Fingerprint
Keywords
- autonomic systems
- Cloud computing
- elasticity
- scalability
ASJC Scopus subject areas
- Computer Science(all)
- Theoretical Computer Science
Cite this
Database scalability, elasticity, and autonomy in the cloud (Extended abstract). / Agrawal, Divyakant; El Abbadi, Amr; Das, Sudipto; Elmore, Aaron J.
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 6587 LNCS PART 1. ed. 2011. p. 2-15 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 6587 LNCS, No. PART 1).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - Database scalability, elasticity, and autonomy in the cloud (Extended abstract)
AU - Agrawal, Divyakant
AU - El Abbadi, Amr
AU - Das, Sudipto
AU - Elmore, Aaron J.
PY - 2011/4/28
Y1 - 2011/4/28
N2 - Cloud computing has emerged as an extremely successful paradigm for deploying web applications. Scalability, elasticity, pay-per-use pricing, and economies of scale from large scale operations are the major reasons for the successful and widespread adoption of cloud infrastructures. Since a majority of cloud applications are data driven, database management systems (DBMSs) powering these applications form a critical component in the cloud software stack. In this article, we present an overview of our work on instilling these above mentioned "cloud features" in a database system designed to support a variety of applications deployed in the cloud: designing scalable database management architectures using the concepts of data fission and data fusion, enabling lightweight elasticity using low cost live database migration, and designing intelligent and autonomic controllers for system management without human intervention.
AB - Cloud computing has emerged as an extremely successful paradigm for deploying web applications. Scalability, elasticity, pay-per-use pricing, and economies of scale from large scale operations are the major reasons for the successful and widespread adoption of cloud infrastructures. Since a majority of cloud applications are data driven, database management systems (DBMSs) powering these applications form a critical component in the cloud software stack. In this article, we present an overview of our work on instilling these above mentioned "cloud features" in a database system designed to support a variety of applications deployed in the cloud: designing scalable database management architectures using the concepts of data fission and data fusion, enabling lightweight elasticity using low cost live database migration, and designing intelligent and autonomic controllers for system management without human intervention.
KW - autonomic systems
KW - Cloud computing
KW - elasticity
KW - scalability
UR - http://www.scopus.com/inward/record.url?scp=79955105254&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=79955105254&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-20149-3_2
DO - 10.1007/978-3-642-20149-3_2
M3 - Conference contribution
AN - SCOPUS:79955105254
SN - 9783642201486
VL - 6587 LNCS
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 2
EP - 15
BT - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
ER -