Augmented Petri Net Cost Model for Optimisation of Large Bioinformatics Workflows Using Cloud
Augmented Petri Net Cost Model for Optimisation of Large Bioinformatics Workflows Using Cloud
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DOI：
10.1109/ems.2013.35
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发表时间：
2013-11
期刊：
影响因子：
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通讯作者：
Zheng Xie;Liangxiu Han;R. Baldock
中科院分区：
文献类型：
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作者：
Zheng Xie;Liangxiu Han;R. Baldock
本文关注的是，当使用云资源实现大型生物信息学或其他工作流时，存储中间数据的成本和重新生成此数据所产生的计算成本之间可能存在的权衡。实现可能需要删除一些数据以将存储成本保持在预算范围内，并且决定如何以最小的计算成本增加来最好地做到这一点可能会导致复杂的问题。为了解决这些问题，一个修改后的形式的Petri网的工作流建模，并允许应用优化算法来解决可能出现的几种类型的问题。所提出的“增强Petri网”模拟工作流程的成本模型，从而提供了一个平台的优化过程。举例说明，这种优化可以实现在一些不同的情况下，降低整体成本。
This paper concerns the trade-off that may be madebetween the cost of storing intermediate data and thecomputing costs incurred in regenerating this data when large bioinformatics or other workflows are implemented using cloud resources. The implementation may be required todelete some data to keep storage costs within a budget, anddeciding how best to do this with minimal increase incomputing costs can cause complex problems. To addressthese problems, a modified form of Petri net is introduced for modeling the workflow and allowing an optimization algorithm to be applied for addressing several types of problem that may arise. The proposed 'augmented Petri-net' simulates workflows with cost models included, thus providing a platform for an optimization procedure. Illustrations are presented to show that such optimization can achieve overall cost reductions in a number of different scenarios.