Title
A genetic algorithm for power-aware virtual machine allocation in private cloud
Abstract
Energy efficiency has become an important measurement of scheduling algorithm for private cloud. The challenge is trade-off between minimizing of energy consumption and satisfying Quality of Service (QoS) (e.g. performance or resource availability on time for reservation request). We consider resource needs in context of a private cloud system to provide resources for applications in teaching and researching. In which users request computing resources for laboratory classes at start times and non-interrupted duration in some hours in prior. Many previous works are based on migrating techniques to move online virtual machines (VMs) from low utilization hosts and turn these hosts off to reduce energy consumption. However, the techniques for migration of VMs could not use in our case. In this paper, a genetic algorithm for power-aware in scheduling of resource allocation (GAPA) has been proposed to solve the static virtual machine allocation problem (SVMAP). Due to limited resources (i.e. memory) for executing simulation, we created a workload that contains a sample of one-day timetable of lab hours in our university. We evaluate the GAPA and a baseline scheduling algorithm (BFD), which sorts list of virtual machines in start time (i.e. earliest start time first) and using best-fit decreasing (i.e. least increased power consumption) algorithm, for solving the same SVMAP. As a result, the GAPA algorithm obtains total energy consumption is lower than the baseline algorithm on simulated experimentation.
Year
DOI
Venue
2013
10.1007/978-3-642-36818-9_19
ICT-EurAsia'13 Proceedings of the 2013 international conference on Information and Communication Technology
Keywords
DocType
Volume
total energy consumption,baseline algorithm,increased power consumption,start time,energy consumption,private cloud,genetic algorithm,baseline scheduling algorithm,gapa algorithm,power-aware virtual machine allocation,earliest start time,energy efficiency
Conference
abs/1302.4519
ISSN
Citations 
PageRank 
Information and Communication Technology, Lecture Notes in Computer Science, Vol. 7804, Information Systems and Applications, incl. Internet/Web, and HCI, IFIP-LNCS Volumes, ISBN 978-3-642-36817-2, 2013, XVI, 552 p. 170 illus
23
0.84
References 
Authors
11
5
Name
Order
Citations
PageRank
Nguyen Quang-Hung1506.06
Pham Dac Nien2230.84
Nguyen Hoai Nam3231.18
Nguyen Huynh Tuong4514.60
Nam Thoai57018.86