Name
Abstract | ||
|---|---|---|
Energy consumption of cloud data centers accounts for a major operational cost. This paper presents an optimization model for task scheduling to minimize task processing time and energy consumption in data centers for cloud computing. We formulate an integer programming optimization problem to minimize the expected energy consumption of homogenous tasks in a data center with a large number of servers and propose the most-efficient-server first greedy task scheduling algorithm to minimize energy expenditure. We show that the proposed task scheduling can minimize the energy expenditure while bounding the average task waiting time. We present a simulation of the proposed task scheduling scheme to show an optimum number of servers to achieve small task processing times and to minimize energy consumption. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1109/NCA.2012.42 | NCA |
Keywords | Field | DocType |
server assignment,energy consumption,data center,homogenous task,task processing time,small task processing time,greedy task scheduling algorithm,proposed task scheduling scheme,proposed task scheduling,average task,energy expenditure,integer programming,energy,cloud computing,resource management,scheduling,optimization,energy conservation,servers | Mathematical optimization,Energy conservation,Computer science,Scheduling (computing),Server,Integer programming,Energy consumption,Data center,Optimization problem,Cloud computing,Distributed computing | Conference |
Citations | PageRank | References |
6 | 0.48 | 10 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ning Liu | 1 | 21 | 1.13 |
| Ziqian Dong | 2 | 101 | 13.99 |
| Roberto Rojas-Cessa | 3 | 308 | 47.00 |