S. M., Argungu and Che Mohamed Arif, Ahmad Suki and Omar, Mohd Hasbullah (2015) Survey on job scheduling mechanisms in grid environment. ARPN Journal of Engineering and Applied Sciences, 10 (15). pp. 6654-6661. ISSN 1819-6608

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Abstract

Grid systems provide geographically distributed resources for both computational intensive and data-intensive applications.These applications generate large data sets.However, the high latency imposed by the underlying technologies; upon which the grid system is built (such as the Internet and WWW), induced impediment in the effective access to such huge and widely distributed data.To minimize this impediment, jobs need to be scheduled across grid environments to achieve efficient data access.Scheduling multiple data requests submitted by grid users onto the grid environment is NP-hard.Thus, there is no best scheduling algorithm that cuts across all grids computing environments.Job scheduling is one of the key research area in grid computing.In the recent past many researchers have proposed different mechanisms to help scheduling of user jobs in grid systems.Some characteristic features of the grid components; such as machines types and nature of jobs at hand means that a choice needs to be made for an appropriate scheduling algorithm to march a given grid environment.The aim of scheduling is to achieve maximum possible system throughput and to match the application needs with the available computing resources.This paper is motivated by the need to explore the various job scheduling techniques alongside their area of implementation.The paper will systematically analyze the strengths and weaknesses of some selected approaches in the area of grid jobs scheduling.This helps researchers better understand the concept of scheduling, and can contribute in developing more efficient and practical scheduling algorithms.This will also benefit interested researchers to carry out further work in this dynamic research area.

Item Type:	Article
Uncontrolled Keywords:	data grids, job scheduling, data replication.
Subjects:	Q Science > QA Mathematics
Divisions:	School of Computing
Depositing User:	Dr. Ahmad Suki Che Mohamed Arif
Date Deposited:	17 Jan 2017 08:44
Last Modified:	17 Jan 2017 08:44
URI:	https://repo.uum.edu.my/id/eprint/20632

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