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A Novel Static Task Scheduling Algorithm in Distributed Computing Environment

机译:分布式计算环境中的一种新型静态任务调度算法

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Distributed computing environment composed of interconnected machines with varied or same computational capabilities is well suited to meet the computational demands of diverse groups of tasks. The most popular model characterizing tasks' dependence is to utilize DAG (directed acyclic graph). In paper [12], a novel model called TTIG that is more realistic and universal than DAG and its corresponding algorithm called MATE for static mapping of parallel application are presented. We extend TTIG model, and propose a new static scheduling algorithm called GBHA (Group-based Hybrid Algorithm) and two versions (GBHA1 for homogeneous systems and GBHA2 for heterogeneous systems). In this work, our algorithms are compared with MATE and some well-known scheduling algorithms for multiprocessor systems based on DAG. The simulation experiment results show that our algorithms outperform MATE significantly in both homogeneous and heterogeneous systems and can be comparable to efficient scheduling algorithms based on DAG in multiprocessor systems but with much lower complexity.
机译:分布式计算环境由具有不同或相同的计算能力的互联机组成,非常适合满足各种任务组的计算需求。最受欢迎的模型表征任务的依赖性是利用DAG(定向非循环图)。在纸质[12]中,提出了一种名为Ttig的新型模型,该模型是比DAG更现实和普及的,其对应于并行应用程序的静态映射的相应算法。我们扩展了Ttig模型,并提出了一种新的静态调度算法,称为GBHA(基于组的混合算法)和两个版本(用于均匀系统的GBHA1和异构系统的GBHA2)。在这项工作中,将我们的算法与基于DAG的多处理器系统的配偶和一些众所周知的调度算法进行比较。仿真实验结果表明,我们的算法在均匀和异构系统中显着优于伴随着伴侣,并且可以与多处理器系统中的DAG的有效调度算法相当,但复杂性大得多。

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