2015 15th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing 2015
DOI: 10.1109/ccgrid.2015.97
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A Priority-Based Scheduling Heuristic to Maximize Parallelism of Ready Tasks for DAG Applications

Abstract: Abstract-In practical Cloud/Grid computing systems, DAG scheduling may be faced with challenges arising from severe uncertainty about the underlying platform. For instance, it could be hard to have explicit information about task execution time and/or the availability of resources; both may change dynamically, in difficult to predict ways. In such a setting, the development of various kinds of just-in-time scheduling schemes, which aim at maximizing the parallelism of ready tasks of DAG, seems to be a promisin… Show more

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Cited by 12 publications
(2 citation statements)
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“…In this paper, we supposed off-line scheduling instead of on-line scheduling where tasks are assigned to processor after becoming ready to be executed, e.g., the method proposed in [12]. We assumed that a job is expressed as a directed acyclic graph (DAG), which is known as a workflow type job.…”
Section: A System Modelmentioning
confidence: 99%
“…In this paper, we supposed off-line scheduling instead of on-line scheduling where tasks are assigned to processor after becoming ready to be executed, e.g., the method proposed in [12]. We assumed that a job is expressed as a directed acyclic graph (DAG), which is known as a workflow type job.…”
Section: A System Modelmentioning
confidence: 99%
“…In [8], the authors considered information of tasks (i.e., task completion time and size of tasks) and the information is used in the self-adaptive scheduling technique to reduce total processing time and average response time. To solve dependency issues of cloud tasks, the scheduling problem can be translated to the directed acyclic graph (DAG) [9]. To address the performance issue, the authors of [10] proposed a prioritizing scheme of the DAG of tasks and the authors of [11] proposed an AREA-Oriented scheduling (AO-scheduling) to compensate the defects of cloud based scheduling problems.…”
Section: Categorymentioning
confidence: 99%