Paper Info
Title
Task Scheduling and Server Provisioning for Energy-Efficient Cloud-Computing Data Centers
Abstract
In this paper, we present an optimization model for task scheduling for minimizing energy consumption in cloud-computing data centers. The proposed approach was formulated as an integer programming problem to minimize the cloud-computing data center energy consumption by scheduling tasks to a minimum numbers of servers while keeping the task response time constraints. We prove that the average task response time and the number of active servers needed to meet such time constraints are bounded through the use of a greedy task-scheduling scheme. In addition, we propose the most-efficient server- first task-scheduling scheme to minimize energy expenditure as a practical scheduling scheme. We model and simulate the proposed scheduling scheme for a data center with heterogeneous tasks. The simulation results show that the proposed task-scheduling scheme reduces server energy consumption on average over 70 times when compared to the energy consumed under a (not-optimized) random-based task-scheduling scheme. We show that energy savings are achieved by minimizing the allocated number of servers.
Year
DOI
Venue
2013
10.1109/ICDCSW.2013.68
ICDCS Workshops
Keywords
DocType
ISSN
task response time constraints,energy savings,energy expenditure,power aware computing,practical scheduling scheme,scheduling,task scheduling,computer centres,integer programming,average task response time,random-based task-scheduling scheme,cloud-computing data center energy,cloud computing,energy saving,greedy task-scheduling scheme,energy,proposed scheduling scheme,greedy algorithm,server energy consumption,optimization model,energy expenditure minimization,server provisioning,energy consumption minimization,server-first task-scheduling scheme,energy-efficient cloud-computing data centers,green data centers,proposed taskscheduling scheme,energy consumption,heterogeneous tasks,scheduling tasks,integer programming problem,data models,optimization,histograms,servers
Conference
1545-0678
ISBN
Citations 
PageRank 
978-1-4799-3247-4
10
0.80
References 
Authors
13
3
Name
Order
Citations
PageRank
Ning Liu1100.80
Ziqian Dong210113.99
Roberto Rojas-Cessa330847.00