Name
Abstract | ||
|---|---|---|
Workload management is the discipline of effectively managing, controlling, and monitoring work flow across computing systems. It is an increasingly important requirement of database management systems (DBMSs) in view of the trends towards server consolidation and more diverse workloads. Workload management is necessary so the DBMS can be business-objective oriented, can provide efficient differentiated service at fine granularity, and can maintain high utilization of resources with low management costs. The authors see that workload management is shifting from offline planning to online adaptation. In this article, the authors discuss the objectives of workload management in autonomic DBMSs and provide a framework for examining how current workload management mechanisms match up with these objectives. They then use the framework to study several mechanisms from both DBMS products and research efforts. They also propose directions for future work in the area of workload management for autonomic DBMSs. [Article copies are available for purchase from InfoSci-on-Demand.com] |
Year | DOI | Venue |
|---|---|---|
2009 | 10.4018/jdm.2009070101 | JOURNAL OF DATABASE MANAGEMENT |
Keywords | Field | DocType |
Autonomic Computing,Workload Characterization,Workload Management | Data mining,Autonomic computing,Computer science,Knowledge management,Differentiated service,Granularity,Work flow,Online adaptation,Computing systems,Workload management,Process management | Journal |
Volume | Issue | ISSN |
20 | 3 | 1063-8016 |
Citations | PageRank | References |
14 | 0.59 | 13 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Baoning Niu | 1 | 53 | 7.37 |
| Patrick Martin | 2 | 14 | 0.59 |
| Wendy Powley | 3 | 329 | 28.43 |