Name
Title | ||
|---|---|---|
A Resource Usage Prediction-Based Energy-Aware Scheduling Algorithm for Instance-Intensive Cloud Workflows. |
Abstract | ||
|---|---|---|
The applications of instance-intensive workflow are widely used in e-commerce, advanced manufacturing, etc. However, existing studies normally do not consider the problem of reducing energy consumption by utilizing the characters of instance-intensive workflow applications. This paper presents a resource usage Prediction-based Energy-Aware scheduling algorithm, named PEA. Technically, this method improves the energy efficiency of instance-intensive cloud workflow by predicting resources utilization and the strategies of batch processing and load balancing. The efficiency and effectiveness of the proposed algorithm are validated by extensive experiments. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1007/978-3-030-12981-1_44 | CollaborateCom |
Field | DocType | Citations |
Computer science,Load balancing (computing),Efficient energy use,Scheduling (computing),Batch processing,Workflow,Energy consumption,Advanced manufacturing,Distributed computing,Cloud computing | Conference | 0 |
PageRank | References | Authors |
0.34 | 17 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Zhibin Wang | 1 | 0 | 1.69 |
| Yiping Wen | 2 | 25 | 8.59 |
| Yu Zhang | 3 | 294 | 98.00 |
| Jinjun Chen | 4 | 911 | 53.03 |
| Buqing Cao | 5 | 9 | 5.93 |