The Ant Colony Optimization algorithms (ACO) are computational models inspired by the collective foraging behavior of ants. By looking at the strengths of ACO, they are the most appropriate for scheduling of tasks in soft real-time systems. In this paper, ACO based scheduling algorithm for real-time operating systems (RTOS) has been proposed. During simulation, results are obtained with periodic tasks, measured in terms of Success Ratio & Effective CPU Utilization and compared with Kotecha’s algorithm in the same environment. It has been observed that the proposed algorithm is equally optimal during underloaded conditions and it performs better during overloaded conditions.
| Published in |
International Journal of Intelligent Information Systems (Volume 4, Issue 2-1)
This article belongs to the Special Issue Logistics Optimization Using Evolutionary Computation Techniques |
| DOI | 10.11648/j.ijiis.s.2015040201.13 |
| Page(s) | 13-17 |
| Creative Commons |
This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited. |
| Copyright |
Copyright © The Author(s), 2024. Published by Science Publishing Group |
Real-Time Systems, Scheduling, ACO, EDF
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APA Style
Cheng Zhao, Myungryun Yoo, Takanori Yokoyama. (2015). On-Line Scheduling Algorithm for Real-Time Multiprocessor Systems with ACO. International Journal of Intelligent Information Systems, 4(2-1), 13-17. https://doi.org/10.11648/j.ijiis.s.2015040201.13
ACS Style
Cheng Zhao; Myungryun Yoo; Takanori Yokoyama. On-Line Scheduling Algorithm for Real-Time Multiprocessor Systems with ACO. Int. J. Intell. Inf. Syst. 2015, 4(2-1), 13-17. doi: 10.11648/j.ijiis.s.2015040201.13
AMA Style
Cheng Zhao, Myungryun Yoo, Takanori Yokoyama. On-Line Scheduling Algorithm for Real-Time Multiprocessor Systems with ACO. Int J Intell Inf Syst. 2015;4(2-1):13-17. doi: 10.11648/j.ijiis.s.2015040201.13
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Download@article{10.11648/j.ijiis.s.2015040201.13,
author = {Cheng Zhao and Myungryun Yoo and Takanori Yokoyama},
title = {On-Line Scheduling Algorithm for Real-Time Multiprocessor Systems with ACO},
journal = {International Journal of Intelligent Information Systems},
volume = {4},
number = {2-1},
pages = {13-17},
doi = {10.11648/j.ijiis.s.2015040201.13},
url = {https://doi.org/10.11648/j.ijiis.s.2015040201.13},
eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijiis.s.2015040201.13},
abstract = {The Ant Colony Optimization algorithms (ACO) are computational models inspired by the collective foraging behavior of ants. By looking at the strengths of ACO, they are the most appropriate for scheduling of tasks in soft real-time systems. In this paper, ACO based scheduling algorithm for real-time operating systems (RTOS) has been proposed. During simulation, results are obtained with periodic tasks, measured in terms of Success Ratio & Effective CPU Utilization and compared with Kotecha’s algorithm in the same environment. It has been observed that the proposed algorithm is equally optimal during underloaded conditions and it performs better during overloaded conditions.},
year = {2015}
}
TY - JOUR T1 - On-Line Scheduling Algorithm for Real-Time Multiprocessor Systems with ACO AU - Cheng Zhao AU - Myungryun Yoo AU - Takanori Yokoyama Y1 - 2015/01/29 PY - 2015 N1 - https://doi.org/10.11648/j.ijiis.s.2015040201.13 DO - 10.11648/j.ijiis.s.2015040201.13 T2 - International Journal of Intelligent Information Systems JF - International Journal of Intelligent Information Systems JO - International Journal of Intelligent Information Systems SP - 13 EP - 17 PB - Science Publishing Group SN - 2328-7683 UR - https://doi.org/10.11648/j.ijiis.s.2015040201.13 AB - The Ant Colony Optimization algorithms (ACO) are computational models inspired by the collective foraging behavior of ants. By looking at the strengths of ACO, they are the most appropriate for scheduling of tasks in soft real-time systems. In this paper, ACO based scheduling algorithm for real-time operating systems (RTOS) has been proposed. During simulation, results are obtained with periodic tasks, measured in terms of Success Ratio & Effective CPU Utilization and compared with Kotecha’s algorithm in the same environment. It has been observed that the proposed algorithm is equally optimal during underloaded conditions and it performs better during overloaded conditions. VL - 4 IS - 2-1 ER -
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