Name
Abstract | ||
|---|---|---|
High performance computing data centers are playing increasingly important roles in our daily life. However, as data centers increase in size and number, the power consumption at the data centers has also increased dramatically. We are facing the challenge of reducing energy consumption, lowering down the peak inlet temperature and at the same time meeting short make span requirements. In this paper, we present two dependent task scheduling algorithms to balance the trade-offs among data center's power consumption, peak inlet temperature, and application's make span. We compare them with two existing algorithms, i.e., the List algorithm and the Coolest Inlets algorithms. Our extensive simulations show clear advantages of the proposed approaches over the List and the Coolest Inlets algorithms for both homogeneous and heterogeneous data centers. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1109/GreenCom.2011.12 | GreenCom |
Keywords | Field | DocType |
makespan aware dependent task,list algorithm,energy consumption,data centers increase,data center,high performance computing data,span requirement,coolest inlets algorithm,peak inlet temperature,power consumption,heterogeneous data center,data centers,scheduling,scheduling algorithm,heating,consumption,servers | Job shop scheduling,Supercomputer,Homogeneous,Computer science,Scheduling (computing),Server,Real-time computing,Data center,Energy consumption,Power consumption,Distributed computing | Conference |
Citations | PageRank | References |
2 | 0.40 | 7 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Zheng Li | 1 | 2 | 2.76 |
| Li Wang | 2 | 40 | 5.11 |
| Shangping Ren | 3 | 497 | 57.72 |
| Gang Quan | 4 | 945 | 66.11 |