NDLI: Improving job scheduling performance with parallel access to replicas in Data Grid environment

Content Provider	Springer Nature Link
Author	Zhang, Junwei Lee, Bu Sung Tang, Xueyan Yeo, Chai Kiat
Copyright Year	2009
Abstract	Data Grid has evolved to be the solution for data-intensive applications, such as High Energy Physics (HEP), astrophysics, and computational genomics. These applications usually have large input of data to be analyzed and these input data are widely replicated across Data Grid to improve the performance. The job scheduling performance on traditional computing jobs can be studied using queuing theory. However, with the addition of data transfer, the job scheduling performance is too complex to be modeled. In this research, we study the impact of data transfer on the performance of job scheduling in the Data Grid environment. We have proposed a parallel downloading system that supports replicating data fragments and parallel downloading of replicated data fragments, to improve the job scheduling performance. The performance of the parallel downloading system is compared with non-parallel downloading system, using three scheduling heuristics: Shortest Turnaround Time (STT), Least Relative Load (LRL) and Data Present (DP). Our simulation results show that the proposed parallel download approach greatly improves the Data Grid performance for all three scheduling algorithms, in terms of the geometric mean of job turnaround time. The advantage of parallel downloading system is most evident when the Data Grid has relatively low network bandwidth and relatively high computing power.
Starting Page	245
Ending Page	269
Page Count	25
File Format	PDF
ISSN	09208542
Journal	The Journal of Supercomputing
Volume Number	56
Issue Number	3
e-ISSN	15730484
Language	English
Publisher	Springer US
Publisher Date	2009-11-27
Publisher Place	Boston
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Computer Science Processor Architectures Programming Languages, Compilers, Interpreters
Content Type	Text
Resource Type	Article
Subject	Theoretical Computer Science Information Systems Hardware and Architecture Software

Sl.	Authority	Responsibilities	Communication Details
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
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

Job scheduling and dynamic data replication in data grid environment

A performance-based parallel loop scheduling on grid environments

An efficient grid scheduling strategy for data parallel applications

Fault-aware grid scheduling using performance prediction by workload modeling

High performance I/O architectures and systems

Enhancing list scheduling heuristics for dependent job scheduling in grid computing environments

Enhancing genetic algorithms for dependent job scheduling in grid computing environments

Dynamic replication strategies in data grid systems: a survey

Improving A Solution's Quality Through Parallel Processing

Improving job scheduling performance with parallel access to replicas in Data Grid environment

Similar Documents

Job scheduling and dynamic data replication in data grid environment

A performance-based parallel loop scheduling on grid environments

An efficient grid scheduling strategy for data parallel applications

Fault-aware grid scheduling using performance prediction by workload modeling

High performance I/O architectures and systems

Enhancing list scheduling heuristics for dependent job scheduling in grid computing environments

Enhancing genetic algorithms for dependent job scheduling in grid computing environments

Dynamic replication strategies in data grid systems: a survey

Improving A Solution's Quality Through Parallel Processing

Improving job scheduling performance with parallel access to replicas in Data Grid environment