Abstract
"Problem-solving environments" recently became a widely accepted approach to providing computational resources to solve com-plex eScience problems. This approach represents a problem as a work-ow, orchestrating a set of various computational services. The existing cloud computing resources planning methods do not take into account arelation between such services, problem domain speciffics, predicted work-ow execution timespan, etc. On the other hand, usage of cloud system provides efficient HPC resources usage, distributing tasks on the most suitable resources. Therefore, we need to develop algorithms that provide efficient cloud system resources usage and take into account domain-specific information of the problem.
| Original language | English |
|---|---|
| Pages | 22-28 |
| Number of pages | 7 |
| Publication status | Published - 2016 |
| Event | 2nd Ural Workshop on Parallel, Distributed, and Cloud Computing for Young Scientists - Yekaterinburg, Russian Federation Duration: 6 Oct 2016 → … |
Conference
| Conference | 2nd Ural Workshop on Parallel, Distributed, and Cloud Computing for Young Scientists |
|---|---|
| Abbreviated title | Ural-PDC 2016 |
| Country/Territory | Russian Federation |
| City | Yekaterinburg |
| Period | 6/10/16 → … |
Keywords
- Cloud
- Cloud planning
- Problem-solving environment
- Workow
- Cloud computing
- Clouds
- Distributed computer systems
- Cloud systems
- Cloud-based
- Computational resources
- Computing resource
- Domain-specific information
- Problem domain
- Problem solving environments
- Problem solving