Development of a Model Architecture for Job Scheduling
Science Journal of Circuits, Systems and Signal Processing
Volume 9, Issue 1, June 2020, Pages: 16-23
Received: Mar. 29, 2020;
Accepted: Apr. 22, 2020;
Published: May 19, 2020
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Eduok Uyuho Isaac, Department of Computer Science, Ignatius Ajuru University of Education, Port Harcourt Rivers State, Nigeria
Amannah Constance Izuchukwu, Department of Computer Science, Ignatius Ajuru University of Education, Port Harcourt Rivers State, Nigeria
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Job scheduling has a long history. Job schedulers have been one of the major component of IT infrastructure since the early mainframe system, at first, stacks of punched cards were processed one after the other, hence the term batch processing. The aim of a job scheduler was to arrange, control and optimize work and workload in a production process. The study aimed at achieving a job scheduler that can assign jobs to available resources in such a way that workload leveling can be achieved. The objectives of the study included to; ascertain the existing schedule system, design a model platform for job scheduling, implement the model platform for job scheduling, and test and deploy the model platform for job scheduling. The study adopted the spiral development model. The proposed system was developed using java script which is a client scripting language which is used for creating web and windows application and it has almost all online application since the system is an online system. The developed application was tested with field Meta data and the outcome was according to specification and of desired output. The application was hosted on three different servers, one server for the frontend, another server for the backend and the third server for the database, hosting on the three different servers did the magic by making the system faster and easy to optimize.
Model, Architecture, Job Scheduling, Check off Jobs, Scheduling System, Labor Load Levelling, Optimization
To cite this article
Eduok Uyuho Isaac,
Amannah Constance Izuchukwu,
Development of a Model Architecture for Job Scheduling, Science Journal of Circuits, Systems and Signal Processing. Special Issue: Circuits, Systems, and Signal Processing.
Vol. 9, No. 1,
2020, pp. 16-23.
Copyright © 2020 Authors retain the copyright of this article.
This article is an open access article distributed under the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/
) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Wickens, C. D. (2002). Structured design. IBM Systems Journal, 13 (2), 115–139.
Wickens, C. D. (1984). Processing resources in attention, in R. Parasuraman & D. R. Davies (Eds.), varieties of attention. New York: Academic Press, 63–102.
Gantt, H. L. (1903). A graphical daily balance in manufacture: Transactions of the American. Society of Mechanical Engineers, 24: 1322-1336.
Gantt, H. L. (1916). Algorithms for solving production-scheduling problems, New Haven: Yale University Press.
Pinedo, M. (2002). Scheduling theory algorithms and systems prentice hall, 1-6.
Robert, V. (2005). Multiple resources and performance prediction. Theoretical issues in economics Science. Journal of combinatorics 13 (6), 159–177.
Belenki, A. S., & Levner, E. V (2009). Scheduling models and methods in optimal freight transportation planning. Journal of Automation and Remote Control, 23 (12), 1-56.
Lawler, E. L. (2019). Sequencing jobs to minimize total weighted completion time subject to precedence constraints. Journal of mathematical science, 12 (9), 75–90.
Strand, H. H. (2016). Open shop scheduling for a manufacturing company using machine learning. Journal of artificial intelligence, 10 (5), 123-346.
Tompkins, F. N. (2013). Optimization techniques for task allocation and scheduling in distributed multi-agent operations. Journal of distributed agents, 15 (8), 14-15.
Dror, G. F., & Larry, R. (2007). Job scheduling strategies for parallel processing. Lecture notes in computer science, Michigan press, 17-64.