scholarly journals Reliability-Aware Runtime Adaption Through a Statically Generated Task Schedule

Author(s):  
Laura Rozo ◽  
Aaron Myles Landwehr ◽  
Yan Zheng ◽  
Chengmo Yang ◽  
Guang Gao
Keyword(s):  
2010 ◽  
Vol 2009 (2) ◽  
pp. 19-24
Author(s):  
Xu Liang ◽  
Xingshan Li ◽  
Jinsong Yu

2013 ◽  
Vol 679 ◽  
pp. 77-81 ◽  
Author(s):  
Song Chai ◽  
Yu Bai Li ◽  
Chang Wu ◽  
Jian Wang

Real-time task schedule problem in Chip-Multiprocessor (CMP) receives wide attention in recent years. It is partly because the increasing demand for CMP solutions call for better schedule algorithm to exploit the full potential of hardware, and partly because of the complexity of schedule problem, which itself is an NP-hard problem. To address this task schedule problem, various of heuristics have been studied, among which, Genetic Algorithm (GA), Particle Swarm Optimization (PSO) and Simulated Annealing (SA) are the most popular ones. In this paper, we implement these 3 schedule heuristics, and compare their performance under the context of real-time tasks scheduling on CMP. According to the results of our intensive simulations, PSO has the best fitness optimization of these 3 algorithms, and SA is the most efficient algorithm.


2001 ◽  
Vol 9 (3) ◽  
pp. 444-449 ◽  
Author(s):  
Huaiqing Wang ◽  
Changjun Jiang ◽  
Shaoyi Liao

2013 ◽  
Vol 303-306 ◽  
pp. 2429-2432 ◽  
Author(s):  
Guan Wang ◽  
Hai Cun Yu

Task schedule algorithms directly related to the speed and quality of schedule. Min-Min algorithm always completes the shortest total completion time task first, and has the characteristic of simple and shortest completion time. This paper research scheduling algorithm based on Min—Min algorithm. The result shows that the proposed algorithm is efficient in the cloud computing environment.


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