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A Testing Engine for High-Performance and Cost-Effective Workflow Execution in the Cloud
2015
2015 44th International Conference on Parallel Processing
While pursuing high performance and cost effectiveness for directed acyclic graph (DAG)-structured scientific workflow executions in the cloud, it is critical to identify appropriate resource instances and their quantity. This paper presents a testing engine that employs a resource-selection heuristic, which statically analyzes the DAG structure to guide the selection of resource instances, how many and which ones. The testing engine combines the heuristic with two platformindependent
doi:10.1109/icpp.2015.94
dblp:conf/icpp/PallipuramET15
fatcat:dkzwakicvzagvpl2mewxzk365u