Volume 8, Issue 4 (April 2021), Pages: 75-81

----------------------------------------------

 Original Research Paper

 Title: Dynamic approach to minimize overhead and response time in scheduling periodic real-time tasks

 Author(s): Ahmed A. Alsheikhy *

 Affiliation(s):

 Department of Electrical Engineering, College of Engineering, Northern Border University, Arar, Saudi Arabia

  Full Text - PDF          XML

 * Corresponding Author. 

  Corresponding author's ORCID profile: https://orcid.org/0000-0002-9811-0341

 Digital Object Identifier: 

 https://doi.org/10.21833/ijaas.2021.04.009

 Abstract:

In real-time systems, a task or a set of tasks needs to be executed and completed successfully within a predefined time. Those systems require a scheduling technique or a set of scheduling methods to distribute the given task or the set of tasks among different processors or on a processor. In this paper, a new novel scheduling approach to minimize the overhead from context switching between several periodic tasks is presented. This method speeds up a required response time while ensuring that all tasks meet their deadline times and there is no deadline miss occurred. It is a dynamic-priority technique that works either on a uniprocessor or several processors. In particular, it is proposed to be applied on multiprocessor environments since many applications run on several processors. Various examples are presented within this paper to demonstrate its optimality and efficiency. In addition, several comparison experiments with an earlier version of this approach were performed to demonstrate its efficiency and effectiveness too. Those experiments showed that this novel approach sped up the execution time from 15% to nearly around 46%. In addition, it proved that it reduced the number of a context switch between tasks from 12% to around 50% as shown from simulation tests. Furthermore, this approach delivered all tasks/jobs successfully and ensured there was no deadline miss happened. 

 © 2021 The Authors. Published by IASE.

 This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

 Keywords: Scheduling, Hard real-time systems, Overhead, Response time, Dynamic-priority algorithm

 Article History: Received 19 August 2020, Received in revised form 19 December 2020, Accepted 20 December 2020

 Acknowledgment:

No Acknowledgment.

 Compliance with ethical standards

 Conflict of interest: The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

 Citation:

  Alsheikhy AA (2021). Dynamic approach to minimize overhead and response time in scheduling periodic real-time tasks. International Journal of Advanced and Applied Sciences, 8(4): 75-81

 Permanent Link to this page

 Figures

 Fig. 1 Fig. 2 Fig. 3 Fig. 4 Fig. 5 

 Tables

 Table 1 Table 2 Table 3 Table 4 Table 5 Table 6 Table 7 Table 8 Table 9 

----------------------------------------------

 References (7)

1. Alsheikhy A, Elfouly R, Alharthi M, Ammar R, and Alshegaifi A (2016). An effective real-time dynamic scheduling approach for periodic tasks. International Journal of Computing, Communications and Instrumentation Engineering, 3(2): 279-383.   [Google Scholar]
2. Guo Z and Baruah SK (2015). A neurodynamic approach for real-time scheduling via maximizing piecewise linear utility. IEEE Transactions on Neural Networks and Learning Systems, 27(2): 238-248. https://doi.org/10.1109/TNNLS.2015.2466612   [Google Scholar] PMid:26336153
3. Harkut DG and Agrawal AM (2014). Comparison of different task scheduling algorithms in RTOS: A survey. International Journal of Advanced Research in Computer Science and Software Engineering, 4(7): 1236-1240.   [Google Scholar]
4. Hwang M, Choi D, and Kim P (2011). Least slack time rate first: An efficient scheduling algorithm for pervasive computing environment. Journal of Universal Computer Science, 17(6): 912-925.   [Google Scholar]
5. Kim J, Lee S, and Shin H (2013). Effective task scheduling for embedded systems using iterative cluster slack optimization. Circuits and Systems, 4(8): 479-488. https://doi.org/10.4236/cs.2013.48063   [Google Scholar]
6. Ren J and Phan LTX (2015). Mixed-criticality scheduling on multiprocessors using task grouping. In the 27^th Euromicro Conference on Real-Time Systems, IEEE, Lund, Sweden: 25-34. https://doi.org/10.1109/ECRTS.2015.10   [Google Scholar]
7. Vora V and Somkuwar A (2012). Implementation and performance analysis of real time scheduling algorithms for three industrial embedded applications. International Journal of Information Technology Convergence and Services, 2(6): 1-10. https://doi.org/10.5121/ijitcs.2012.2601   [Google Scholar]