Paper Info
Title
Greedy scheduling of tasks with time constraints for energy-efficient cloud-computing data centers
Abstract
In this paper, we introduce a model of task scheduling for a cloud-computing data center to analyze energy-efficient task scheduling. We formulate the assignments of tasks to servers as an integer-programming problem with the objective of minimizing the energy consumed by the servers of the data center. We prove that the use of a greedy task scheduler bounds the constraint service time whilst minimizing the number of active servers. As a practical approach, we propose the most-efficient-server-first task-scheduling scheme to minimize energy consumption of servers in a data center. Most-efficient-server-first schedules tasks to a minimum number of servers while keeping the data-center response time within a maximum constraint. We also prove the stability of most-efficient-server-first scheme for tasks with exponentially distributed, independent, and identically distributed arrivals. Simulation results show that the server energy consumption of the proposed most-efficient-server-first scheduling scheme is 70 times lower than that of a random-based task-scheduling scheme.
Year
DOI
Venue
2015
10.1186/s13677-015-0031-y
J. Cloud Computing
Keywords
Field
DocType
Cloud computing, Energy efficiency, Data center, Greedy algorithm, Integer programming
Efficient energy use,Scheduling (computing),Computer science,Server,Greedy algorithm,Theoretical computer science,Real-time computing,Schedule,Data center,Energy consumption,Distributed computing,Cloud computing
Journal
Volume
Issue
ISSN
4
1
2192-113X
Citations 
PageRank 
References 
15
0.65
22
Authors
3
Name
Order
Citations
PageRank
Ziqian Dong110113.99
Ning Liu2211.13
Roberto Rojas-Cessa330847.00