An Alternative Way to Analyze Workflow Graphs
CAiSE '02 Proceedings of the 14th International Conference on Advanced Information Systems Engineering
Workflow Management: Models, Methods, and Systems
Workflow Management: Models, Methods, and Systems
Taverna: lessons in creating a workflow environment for the life sciences: Research Articles
Concurrency and Computation: Practice & Experience - Workflow in Grid Systems
Performance Analysis Using Stochastic Petri Nets
IEEE Transactions on Computers
SimGrid: A Generic Framework for Large-Scale Distributed Experiments
UKSIM '08 Proceedings of the Tenth International Conference on Computer Modeling and Simulation
Accurate performance estimation for stochastic marked graphs by bottleneck regrowing
EPEW'10 Proceedings of the 7th European performance engineering conference on Computer performance engineering
Automating Data-Throttling Analysis for Data-Intensive Workflows
CCGRID '12 Proceedings of the 2012 12th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (ccgrid 2012)
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In data intensive workflows, which often involve files, transfer between tasks is typically accomplished as fast as the network links allow, and once transferred, the files are buffered/stored at their destination. Where a task requires multiple files to execute (from different previous tasks), it must remain idle until all files are available. Hence, network bandwidth and buffer/storage within a workflow are often not used effectively. In this paper, we are quantitatively measuring the impact that applying an intelligent data movement policy can have on buffer/storage in comparison with existing approaches. Our main objective is to propose a metric that considers a workflow structure expressed as a Directed Acyclic Graph (DAG), and performance information collected from historical past executions of the considered workflow. This metric is intended for use at the design-stage, to compare various DAG structures and evaluate their potential for optimisation (of network bandwidth and buffer use).