| Project/Area Number |
25540007
|
|---|
| Research Category |
Grant-in-Aid for Challenging Exploratory Research
|
| Allocation Type | Multi-year Fund |
|---|
| Research Field |
Mathematical informatics
|
|---|
| Research Institution | Nara Institute of Science and Technology |
|---|
Principal Investigator |
KASAHARA Shoji 奈良先端科学技術大学院大学, 情報科学研究科, 教授 (20263139)
|
|---|
| Co-Investigator(Renkei-kenkyūsha) |
MASUYAMA Hiroyuki 京都大学, 大学院情報学研究科, 准教授 (60378833)
TACHIBANA Takuji 福井大学, 大学院工学研究科, 准教授 (20415847)
|
|---|
| Project Period (FY) |
2013-04-01 – 2015-03-31
|
| Project Status |
Completed (Fiscal Year 2014)
|
| Budget Amount *help |
¥3,770,000 (Direct Cost: ¥2,900,000、Indirect Cost: ¥870,000)
Fiscal Year 2014: ¥1,690,000 (Direct Cost: ¥1,300,000、Indirect Cost: ¥390,000)
Fiscal Year 2013: ¥2,080,000 (Direct Cost: ¥1,600,000、Indirect Cost: ¥480,000)
|
|---|
| Keywords | 情報基礎 / クラウド・コンピューティング / 極値理論 / タスク・スケジューリング / 性能解析 |
|---|
| Outline of Final Research Achievements |
This study considered the risk-theory-based analysis of task scheduling for large-scale parallel distributed computing. It was found that in task replication, the optimal number of replications which achieves the shortest task-processing time mainly depends on the coefficient of variation of the worker-processing time, and that three replications are sufficient to guarantee a low variance of the task-processing time. In terms of backup-task scheduling, we analyzed system performance by extreme value theory. It was found that a small deadline time is effective for reducing energy consumption when the subtask-processing time follows a heavy-tailed distribution. In case of light-tailed subtask-processing time, on the other hand, energy consumption can be reduced by a large deadline time.
|
