Name
Abstract | ||
|---|---|---|
In today's database server environments, multiple types of workloads can be present in a system simultaneously. Workload types may include on-line transaction processing and business intelligence. Workloads may also have different levels of business importance and distinct performance objectives, which are typically derived from service level agreements. An autonomic workload management system for database management systems (DBMSs) dynamically monitors and controls the flow of the workloads to help DBMSs achieve the desired performance objectives. In this paper, we present a framework and a prototype implementation for autonomic workload management in DBMSs. The framework and the prototype provide the ability to achieve performance objectives of workloads with diverse characteristics, different levels of business importance and varying resource demands while protecting DBMSs against performance failure. The prototype system is implemented on top of IBM (R) DB2 (R) Workload Manager. Initial experiments using the prototype system are presented to demonstrate the effectiveness of the framework. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1515/itit-2014-1016 | IT-INFORMATION TECHNOLOGY |
Keywords | DocType | Volume |
ACM CCS -> Information systems -> Data, management systems -> Database administration -> Autonomous, database administration -> ACM CCS -> Information, systems -> Data management systems -> Database, administration -> ACM CCS -> Information systems ->, Data management systems -> Database administration., Database utilities and tools -> ACM CCS -> Computing, methodologies -> Artificial intelligence -> Computational, control theory | Journal | 56 |
Issue | ISSN | Citations |
1 | 1611-2776 | 0 |
PageRank | References | Authors |
0.34 | 0 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Mingyi Zhang | 1 | 8 | 3.83 |
| Patrick Martin | 2 | 0 | 0.34 |
| Wendy Powley | 3 | 329 | 28.43 |
| Paul Bird | 4 | 119 | 8.78 |
| David Kalmuk | 5 | 110 | 4.49 |