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primary topic: Performance comparison of least slack time based heuristics for job scheduling on computational grid

Performance comparison of least slack time based heuristics for job scheduling on computational grid
type: AcademicArticle
type: Article
abstract: In recent years, increasing demand for computing has led to the development of computational grid. Typically scheduling challenges tend to be NP-hard problems where there is no optimal solution. The research reported here therefore is focused on the development of hybrids scheduling algorithms based on deadline and slack time parameters and its variations, using the concept of optimization techniques. An extensive performance comparison has been presented using real workload traces as benchmark on a grid computational environment. The results were compared with some baseline scheduling approaches in extant literature. The results have shown that the performances of grid scheduling algorithms developed and reported in this paper give good results in most of the cases and also support true scalability, when in the scenario of increasing workload and number of processors on a computational grid environment. © 2014 IEEE.
date: 2014
status: peerReviewed
status: published
author list: authors
type: EPrint
type: ConferenceItemEPrint
is part of: repository

Institute of Electrical and Electronics Engineers Inc.
type: Organization

2014 International Conference on Computer and Information Sciences, ICCOINS 2014 - A Conference of World Engineering, Science and Technology Congress, ESTCON 2014 - Proceedings
type: Collection

J. Okitsu
type: Person
given name: J.
family name: Okitsu

K. Naono
type: Person
given name: K.
family name: Naono

N.B. Zakaria
type: Person
given name: N.B.
family name: Zakaria

A.A. Haruna
type: Person
given name: A.A.
family name: Haruna

L.T. Jung
type: Person
given name: L.T.
family name: Jung

A.J. Pal
type: Person
given name: A.J.
family name: Pal

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primary topic: Performance comparison of least slack time based heuristics for job scheduling on computational grid