Welcome to the InfoSci Platform
Reference Hub1
ACO Based Dynamic Scheduling Algorithm for Real-Time Multiprocessor Systems

ACO Based Dynamic Scheduling Algorithm for Real-Time Multiprocessor Systems

Apurva Shah, Ketan Kotecha
Copyright: © 2013 |Pages: 12
ISBN13: 9781466620650|ISBN10: 146662065X|EISBN13: 9781466620667
DOI: 10.4018/978-1-4666-2065-0.ch006
Cite Chapter Cite Chapter

MLA

Shah, Apurva, and Ketan Kotecha. "ACO Based Dynamic Scheduling Algorithm for Real-Time Multiprocessor Systems." Applications and Developments in Grid, Cloud, and High Performance Computing, edited by Emmanuel Udoh, IGI Global, 2013, pp. 85-96. https://doi.org/10.4018/978-1-4666-2065-0.ch006

APA

Shah, A. & Kotecha, K. (2013). ACO Based Dynamic Scheduling Algorithm for Real-Time Multiprocessor Systems. In E. Udoh (Ed.), Applications and Developments in Grid, Cloud, and High Performance Computing (pp. 85-96). IGI Global. https://doi.org/10.4018/978-1-4666-2065-0.ch006

Chicago

Shah, Apurva, and Ketan Kotecha. "ACO Based Dynamic Scheduling Algorithm for Real-Time Multiprocessor Systems." In Applications and Developments in Grid, Cloud, and High Performance Computing, edited by Emmanuel Udoh, 85-96. Hershey, PA: IGI Global, 2013. https://doi.org/10.4018/978-1-4666-2065-0.ch006

Export Reference

Mendeley
Favorite

Abstract

The Ant Colony Optimization (ACO) algorithms are computational models inspired by the collective foraging behavior of ants. The ACO algorithms provide inherent parallelism, which is very useful in multiprocessor environments. They provide balance between exploration and exploitation along with robustness and simplicity of individual agent. In this paper, ACO based dynamic scheduling algorithm for homogeneous multiprocessor real-time systems is proposed. The results obtained during simulation are measured in terms of Success Ratio (SR) and Effective CPU Utilization (ECU) and compared with the results of Earliest Deadline First (EDF) algorithm in the same environment. It has been observed that the proposed algorithm is very efficient in underloaded conditions and it performs very well during overloaded conditions also. Moreover, the proposed algorithm can schedule some typical instances successfully which are not possible to schedule using EDF algorithm.

Request Access

You do not own this content. Please login to recommend this title to your institution's librarian or purchase it from the IGI Global bookstore.