Efficient Latency Bound Analysis for Data Chains of Real-Time Tasks in Multiprocessor Systems

Author(s):  
Jiankang Ren ◽  
Xin He ◽  
Junlong Zhou ◽  
Hongwei Ge ◽  
Guowei Wu ◽  
...  
2009 ◽  
Vol 20 (10) ◽  
pp. 2628-2636 ◽  
Author(s):  
Jian WANG ◽  
Jian-Ling SUN ◽  
Xin-Yu WANG ◽  
Shen-Kang WANG ◽  
Jun-Bo CHEN

1990 ◽  
Vol 1 (2) ◽  
pp. 184-194 ◽  
Author(s):  
K. Ramamritham ◽  
J.A. Stankovic ◽  
P.-F. Shiah

Author(s):  
Apurva Shah ◽  
Ketan Kotecha

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.


2020 ◽  
pp. 1-1
Author(s):  
Jian-Jia Chen ◽  
Junjie Shi ◽  
Georg Von der Bruggen ◽  
Niklas Ueter

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