Overhead Analysis of Scientific Workflows in Grid Environments

Scientific workflows are a topic of great interest in the grid community that sees in the workflow model an attractive paradigm for programming distributed wide-area grid infrastructures. Traditionally, the grid workflow execution is approached as a pure best effort scheduling problem that maps the...

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Vydané v:IEEE transactions on parallel and distributed systems Ročník 19; číslo 3; s. 378 - 393
Hlavní autori: Prodan, R., Fahringer, T.
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: New York IEEE 01.03.2008
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Predmet:
Computational grids
Concurrent computing
Contracts
Delivery scheduling
distributed applications
Distributed computing
Distributed processing
Distributed systems
distributed/Internet based software engineering tools and techniques
Dynamics
Grid computing
Heuristic
Mathematical models
Middleware
monitors
On-line systems
Online
Operations research
Parallel processing
Performance analysis
performance attributes
performance evaluation
Performance loss
performance measurements
Processor scheduling
Studies
Velocity measurement
Workflow
performance measurements
performance attributes
Distributed systems
performance evaluation
distributed applications
distributed/Internet based software engineering tools and techniques
monitors
ISSN:1045-9219, 1558-2183
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Popis
Shrnutí:Scientific workflows are a topic of great interest in the grid community that sees in the workflow model an attractive paradigm for programming distributed wide-area grid infrastructures. Traditionally, the grid workflow execution is approached as a pure best effort scheduling problem that maps the activities onto the grid processors based on appropriate optimization or local matchmaking heuristics such that the overall execution time is minimized. Even though such heuristics often deliver effective results, the execution in dynamic and unpredictable grid environments is prone to severe performance losses that must be understood for minimizing the completion time or for the efficient use of high-performance resources. In this paper, we propose a new systematic approach to help the scientists and middleware developers understand the most severe sources of performance losses that occur when executing scientific workflows in dynamic grid environments. We introduce an ideal model for the lowest execution time that can be achieved by a workflow and explain the difference to the real measured grid execution time based on a hierarchy of performance overheads for grid computing. We describe how to systematically measure and compute the overheads from individual activities to larger workflow regions and adjust well-known parallel processing metrics to the scope of grid computing, including speedup and efficiency. We present a distributed online tool for computing and analyzing the performance overheads in real time based on event correlation techniques and introduce several performance contracts as quality-of-service parameters to be enforced during the workflow execution beyond traditional best effort practices. We illustrate our method through postmortem and online performance analysis of two real-world workflow applications executed in the Austrian grid environment.
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ISSN:1045-9219
1558-2183
DOI:10.1109/TPDS.2007.70734