Trading off execution time for reliability in scheduling precedence-constrained tasks in heterogeneous computing

Author(s):  
A. Dogan ◽  
F. Ozguner
2013 ◽  
Vol 65 (2) ◽  
pp. 886-902 ◽  
Author(s):  
Hong Jun Choi ◽  
Dong Oh Son ◽  
Seung Gu Kang ◽  
Jong Myon Kim ◽  
Hsien-Hsin Lee ◽  
...  

Author(s):  
Junqiang Jiang ◽  
Chenyan Zhu ◽  
Hailin Cai ◽  
Li Pan ◽  
Wenbin Li ◽  
...  

Efficient workflow scheduling plays a critical role in achieving high performance in heterogeneous distributed computing systems. Given its key importance, workflow scheduling has been extensively studied, and various algorithms have been proposed in the literature mainly for systems with homogeneous or heterogeneous processors. Most of the algorithms leverage the average computation cost to prioritize tasks, and few focus on the combination of the level and out-degree of tasks, which both have a considerable impact on scheduling. A new list scheduling algorithm called level and out-degree earliest finish time (LOEFT) is proposed in this paper to address the problem of static workflow scheduling in a heterogeneous computing environment to reduce the workflow execution time. This algorithm has three major phases: task leveling, task prioritization and processor selection. In the task leveling phase, tasks are categorized into different groups based on depth value to ensure data transmission completeness. In the task prioritizing phase, the upward rank value is combined with the out-degree of every task to calculate the heterogeneous priority rank value on different processors and leverage the value to sort all tasks. In the processor selection phase, the selected task is assigned to the processor, which minimizes the former’s earliest finish time. The experimental simulation of randomly generated DAG and real-world application workflows proves that the LOEFT algorithm can significantly reduce the workflow execution time.


2012 ◽  
Vol 457-458 ◽  
pp. 1039-1046 ◽  
Author(s):  
You Wei Lu ◽  
Zhen Zhen Xu ◽  
Feng Xia

Independent task scheduling algorithms in distributed computing systems deal with three main conflicting factors including load balance, task execution time and scheduling cost. In this paper, the problem of scheduling tasks arriving at a low rate and with long execution time in heterogeneous computing systems is studied, and a new scheduling algorithm based on prediction is proposed. This algorithm evaluates the utility of task scheduling based on statistics and prediction to solve the influence of heterogeneous computing systems. The experimental results reveal that the proposed algorithm adequately balances the conflicting factors, and thus performs better than some classical algorithms such as MCT and MET when the parameters are well selected.


1997 ◽  
Vol 44 (1) ◽  
pp. 35-52 ◽  
Author(s):  
Yan Alexander Li ◽  
John K. Antonio ◽  
Howard Jay Siegel ◽  
Min Tan ◽  
Daniel W. Watson

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