Name
Title | ||
|---|---|---|
Data-Aware Resource Scheduling for Multicloud Workflows: A Fine-Grained Simulation Approach |
Abstract | ||
|---|---|---|
Cloud infrastructures have seen increasing popularity for addressing the growing computational needs of today's scientific and engineering applications. However, resource management challenges exist in the elastic cloud environment, such as resource provisioning and task allocation, especially when data movement between multiple domains plays an important role. In this work, we study the impact of data-aware resource management and scheduling on scientific workflows in multicloud environments. We develop a workflow simulator based on a network simulation framework for fine-grained simulation for workflow computation and data movement. Using the workload traces from a production metagenomic data analysis service, we evaluate different resource scheduling mechanisms, including proposed data-aware scheduling policies under various resource and bandwidth configurations. The results of this work are expected to answer questions about how to provision computing resources for certain workloads efficiently and how to place tasks across multidomain clouds in order to reduce data movement costs for overall improved system performance. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1109/CloudCom.2014.19 | CloudCom |
Keywords | Field | DocType |
data-aware resource management,multicloud environments,scientific application,workload traces,production metagenomic data analysis service,task allocation,scheduling,data-aware resource scheduling,cloud infrastructures,workflow simulation,data analysis,natural sciences computing,resource allocation,bandwidth configuration,workflow simulator,scientific workflows,data-aware scheduling,resource management,workflow computation,data movement,multicloud workflows,fine-grained simulation approach,workflow management software,resource configuration,network simulation framework,cloud computing,resource provisioning,engineering application,scientific workflow,resource scheduling mechanisms,computational modeling,measurement,data models,bandwidth,servers | Resource management,Workflow technology,Fair-share scheduling,Computer science,Real-time computing,Resource allocation,Workflow engine,Workflow,Workflow management system,Distributed computing,Cloud computing | Conference |
ISSN | Citations | PageRank |
2330-2194 | 8 | 0.48 |
References | Authors | |
14 | 9 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Wei Tang | 1 | 152 | 10.65 |
| Jonathan Jenkins | 2 | 20 | 1.69 |
| Folker Meyer | 3 | 484 | 51.83 |
| Robert Ross | 4 | 2717 | 173.13 |
| Rajkumar Kettimuthu | 5 | 770 | 70.13 |
| Linda Winkler | 6 | 238 | 26.68 |
| Xi Yang | 7 | 12 | 1.97 |
| Thomas Lehman | 8 | 8 | 0.48 |
| Narayan Desai | 9 | 319 | 29.73 |