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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Anglano, C. Canonico, M. |
| Copyright Year | 2008 |
| Description | Author affiliation: Dipt. di Inf., Univ. del Piemonte Orientale, Rome (Anglano, C.; Canonico, M.) |
| Abstract | Desktop grids are being increasingly used as the execution platform for a variety of applications that can be structured as bag-of-tasks (BoT). Scheduling BoT applications on desktop grids has thus attracted the attention of the scientific community, and various schedulers tailored towards them have been proposed in the literature. However, previous work has focused on scheduling a single BoT application at a time, thus neglecting other scenarios in which several users submit multiple BoT applications at the same time. This paper aims at filling this gap by proposing a set of scheduling algorithms able to deal with multiple BoT applications. The performance of these algorithm has been evaluated, by means of simulation, for a large set of operational scenarios obtained by varying both the workload submitted to the desktop grid and the characteristics of the involved resources. Our results show that, although there is no a clear winner among the proposed solutions, knowledge-free strategies (that is, strategies that do not require any information concerning the applications or the resources) can provide good performance. |
| Starting Page | 1 |
| Ending Page | 8 |
| File Size | 217383 |
| Page Count | 8 |
| File Format | |
| ISBN | 9781424416936 |
| ISSN | 15302075 |
| DOI | 10.1109/IPDPS.2008.4536445 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2008-04-14 |
| Publisher Place | USA |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Scheduling algorithm Grid computing Application software Processor scheduling Biology computing Computational modeling Fluctuations Filling Internet Large-scale systems |
| Content Type | Text |
| Resource Type | Article |
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