Performance database: capturing data for optimizing distributed streaming workflows-Reference-Cited by-同舟云学术

Performance database: capturing data for optimizing distributed streaming workflows

Published:2011-08-28 Issue:1949 Volume:369 Page:3268-3284
ISSN:1364-503X
Container-title:Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences
language:en
Short-container-title:Phil. Trans. R. Soc. A.

Author:

Liew Chee Sun¹²,Atkinson Malcolm P.¹,Ostrowski Radosław³,Cole Murray¹,van Hemert Jano I.¹⁴,Han Liangxiu⁵

Affiliation:

1. School of Informatics, University of Edinburgh, 10 Crichton Street, Edinburgh EH8 9AB, UK

2. Faculty of Computer Science and Information Technology, University of Malaya, 50603 Kuala Lumpur, Malaysia

3. EPCC, University of Edinburgh, JCMB, The Kings Buildings, Mayfield Road, Edinburgh EH9 3JZ, UK

4. Optos, Queensferry House, Carnegie Campus, Enterprise Way, Dunfermline KY11 8GR, UK

5. School of Computing, Mathematics and Digital Technology, Manchester Metropolitan University, Chester Street, Manchester M1 5GD, UK

Abstract

The performance database (PDB) stores performance-related data gathered during workflow enactment. We argue that, by carefully understanding and manipulating these data, we can improve efficiency when enacting workflows. This paper describes the rationale behind the PDB, and proposes a systematic way to implement it. The prototype is built as part of the Advanced Data Mining and Integration Research for Europe project. We use workflows from real-world experiments to demonstrate the usage of PDB.

Publisher

The Royal Society

Subject

General Physics and Astronomy,General Engineering,General Mathematics

Link

https://royalsocietypublishing.org/doi/pdf/10.1098/rsta.2011.0134

Reference16 articles.

1. Towards optimising distributed data streaming graphs using parallel streams

2. Examining the Challenges of Scientific Workflows

3. Integrating distributed data sources with OGSA–DAI DQP and V iews

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