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Reseach Article

Comparative Study of Task Duplication based Scheduling Algorithms for Parallel Systems

by Nidhi Arora
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 58 - Number 19
Year of Publication: 2012
Authors: Nidhi Arora
10.5120/9394-3835

Nidhi Arora . Comparative Study of Task Duplication based Scheduling Algorithms for Parallel Systems. International Journal of Computer Applications. 58, 19 ( November 2012), 46-48. DOI=10.5120/9394-3835

@article{ 10.5120/9394-3835,
author = { Nidhi Arora },
title = { Comparative Study of Task Duplication based Scheduling Algorithms for Parallel Systems },
journal = { International Journal of Computer Applications },
issue_date = { November 2012 },
volume = { 58 },
number = { 19 },
month = { November },
year = { 2012 },
issn = { 0975-8887 },
pages = { 46-48 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume58/number19/9394-3835/ },
doi = { 10.5120/9394-3835 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:02:59.011139+05:30
%A Nidhi Arora
%T Comparative Study of Task Duplication based Scheduling Algorithms for Parallel Systems
%J International Journal of Computer Applications
%@ 0975-8887
%V 58
%N 19
%P 46-48
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Scheduling of tasks is done by mapping tasks on multiple processors so that it requires least time for completion of all processes. Multiprocessors are used to run real time applications that uniprocessor systems would not be competent to execute. This paper presents various scheduling algorithms that schedule an edge-weighted Directed Acyclic Graph (DAG) to a number of processors. In this paper, task duplication based scheduling algorithms like PY algorithm and DSH algorithm are analyzed and studied for various performance metrices. Also, the effect of varying number of processors is examined on these algorithms.

References
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Index Terms

Computer Science
Information Sciences

Keywords

Task Scheduling DAG Parallel Processing Multiprocessor Scheduling Performance Evaluation Scalability