DocumentCode
1707831
Title
Instrumentation and Trace Analysis for Ad-Hoc Python Workflows in Cloud Environments
Author
Acuna, Ruben ; Lacroix, Zoe ; Bazzi, Rida A.
Author_Institution
Sch. of Comput., Inf., & Decision Syst. Eng., Arizona State Univ., Tempe, AZ, USA
fYear
2015
Firstpage
114
Lastpage
121
Abstract
Knowledge of structure is critical to map legacy workflows to environments suitable to run on the cloud. We present a method which characterizes a workflow structure with the execution trace produced by instrumented logging functionality. The method generates the structure of workflows to support their reuse by permitting their transformation into modern execution environments. The method presented in the paper is implemented for Python workflows and demonstrated in the context of several legacy scientific workflows.
Keywords
cloud computing; object-oriented languages; system monitoring; ad-hoc Python workflows; cloud environments; execution trace analysis; instrumented logging functionality; Bioinformatics; Cloud computing; Instruments; Libraries; Ports (Computers); Proteins; Standards; Python; cloud; instrumentation; scientific application; trace analysis; workflow; workflow graph; workflow structure;
fLanguage
English
Publisher
ieee
Conference_Titel
Cloud Computing (CLOUD), 2015 IEEE 8th International Conference on
Conference_Location
New York City, NY
Print_ISBN
978-1-4673-7286-2
Type
conf
DOI
10.1109/CLOUD.2015.25
Filename
7214035
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