NDLI: Exploiting Spatial Locality to Improve Disk Efficiency in Virtualized Environments

Content Provider	IEEE Xplore Digital Library
Author	Xiao Ling Ibrahim, S. Hai Jin Song Wu Songqiao Tao
Copyright Year	2013
Description	Author affiliation: Cluster & Grid Comput. Lab., Huazhong Univ. of Sci. & Technol., Wuhan, China (Xiao Ling; Hai Jin; Song Wu; Songqiao Tao) \|\| INRIA Rennes - Bretagne Atlantique, Rennes, France (Ibrahim, S.)
Abstract	Virtualization has become a prominent tool in data centers and is extensively leveraged in cloud environments: it enables multiple virtual machines (VMs) - with multiple operating systems and applications - to run within a physical server. However, virtualization introduces the challenging issue of preserving the high disk utilization (i.e., reducing the seek delay and rotation overhead) when allocating disk resources to VMs. Exploiting spatial locality, a key technique for improving disk utilization and performance, faces additional challenges in the virtualized cloud because of the transparency feature of virtualization (hyper visors do not have the information about the access patterns of applications running within each VM). To this end, this paper contributes a novel disk I/O scheduling framework, named Pregather, to improve disk I/O efficiency through exposure and exploitation of the special spatial locality in the virtualized environment (regional and sub-regional spatial locality corresponds to the virtual disk space and applications' access patterns, respectively), thereby improving the performance of disk-intensive applications without harming the transparency feature of virtualization (without a priori knowledge of the applications' access patterns). The key idea behind Pregather is to implement an intelligent model to predict the access regularity of sub-regional spatial locality for each VM. We implement the Pregather disk scheduling framework and perform extensive experiments that involve multiple simultaneous applications of both synthetic benchmarks and a MapReduce application on Xen-based platforms. Our experiments demonstrate the accuracy of our prediction model and indicate that Pregather results in the high disk spatial locality and a significant improvement in disk throughput and application performance.
Sponsorship	IEEE
Starting Page	192
Ending Page	201
File Size	638955
Page Count	10
File Format	PDF
ISBN	9780769551029
ISSN	15267539
DOI	10.1109/MASCOTS.2013.27
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-08-14
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Virtual machine monitors Virtualization Predictive models Analytical models Prediction algorithms Data models Throughput efficiency virtualization disk-intensive I/O scheduling spatial locality
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

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