Managing Uncertainty: A Case for Probabilistic Grid Scheduling
| dc.creator | Lazarevic, Aleksandar | |
| dc.creator | Sacks, Lionel | |
| dc.creator | Prnjat, Ognjen | |
| dc.date | 2007-11-02 | |
| dc.date.accessioned | 2026-07-07T08:40:13Z | |
| dc.date.available | 2026-07-07T08:40:13Z | |
| dc.description | The Grid technology is evolving into a global, service-orientated architecture, a universal platform for delivering future high demand computational services. Strong adoption of the Grid and the utility computing concept is leading to an increasing number of Grid installations running a wide range of applications of different size and complexity. In this paper we address the problem of elivering deadline/economy based scheduling in a heterogeneous application environment using statistical properties of job historical executions and its associated meta-data. This approach is motivated by a study of six-month computational load generated by Grid applications in a multi-purpose Grid cluster serving a community of twenty e-Science projects. The observed job statistics, resource utilisation and user behaviour is discussed in the context of management approaches and models most suitable for supporting a probabilistic and autonomous scheduling architecture. | |
| dc.identifier | https://arxiv.org/abs/0711.0327 | |
| dc.identifier | http://arxiv.org/abs/0711.0327 | |
| dc.identifier.uri | http://salesiana.dossiersoluciones.com/handle/123456789/141313 | |
| dc.subject | Distributed, Parallel, and Cluster Computing | |
| dc.title | Managing Uncertainty: A Case for Probabilistic Grid Scheduling | |
| dc.type | text |