Next Article in Journal
4D Remeshing Using a Space-Time Finite Element Method for Elastodynamics Problems
Next Article in Special Issue
Dual Methods for Optimal Allocation of Telecommunication Network Resources with Several Classes of Users
Previous Article in Journal
Nonlinear Elimination of Drugs in One-Compartment Pharmacokinetic Models: Nonstandard Finite Difference Approach for Various Routes of Administration
Previous Article in Special Issue
Machine Learning-Based Sentiment Analysis for Twitter Accounts
Article Menu
Issue 2 (June) cover image

Export Article

Open AccessArticle
Math. Comput. Appl. 2018, 23(2), 28;

The Impact of the Implementation Cost of Replication in Data Grid Job Scheduling

Department of Computer Science, COMSATS University, University Road, Tobe Camp, Abbottabad 22060, Pakistan
Department for Management of Science and Technology Development, Ton Duc Thang University, Ho Chi Minh City, Vietnam
Faculty of Information Technology, Ton Duc Thang University, Ho Chi Minh City, Vietnam
Department of Computer Science, University of Texas at San Antonio, San Antonio, TX 78249, USA
(Visiting Faculty) Department of Computer Engineering & Informatics, University of Patras, 26504 Rio, Greece
Author to whom correspondence should be addressed.
Received: 11 May 2018 / Revised: 11 May 2018 / Accepted: 16 May 2018 / Published: 25 May 2018
(This article belongs to the Special Issue Applied Modern Mathematics in Complex Networks)
Full-Text   |   PDF [3142 KB, uploaded 30 May 2018]   |  


Data Grids deal with geographically-distributed large-scale data-intensive applications. Schemes scheduled for data grids attempt to not only improve data access time, but also aim to improve the ratio of data availability to a node, where the data requests are generated. Data replication techniques manage large data by storing a number of data files efficiently. In this paper, we propose centralized dynamic scheduling strategy-replica placement strategies (CDSS-RPS). CDSS-RPS schedule the data and task so that it minimizes the implementation cost and data transfer time. CDSS-RPS consists of two algorithms, namely (a) centralized dynamic scheduling (CDS) and (b) replica placement strategy (RPS). CDS considers the computing capacity of a node and finds an appropriate location for the job. RPS attempts to improve file access time by using replication on the basis of number of accesses, storage capacity of a computing node, and response time of a requested file. Extensive simulations are carried out to demonstrate the effectiveness of the proposed strategy. Simulation results demonstrate that the replication and scheduling strategies improve the implementation cost and average access time significantly. View Full-Text
Keywords: data grid; replica placement; replication; scheduling data grid; replica placement; replication; scheduling

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

Share & Cite This Article

MDPI and ACS Style

Nazir, B.; Ishaq, F.; Shamshirband, S.; Chronopoulos, A.T. The Impact of the Implementation Cost of Replication in Data Grid Job Scheduling. Math. Comput. Appl. 2018, 23, 28.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Metrics

Article Access Statistics



[Return to top]
Math. Comput. Appl. EISSN 2297-8747 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top