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An evaluation of biosurveillance grid--dynamic algorithm distribution across multiple computer nodes.

Ming-Chi Tsai¹, Fu-Chiang Tsui, Michael M Wagner

¹RODS Laboratory, Department of Biomedical Informatics, University of Pittsburgh, Pittsburgh, Pennsylvania, USA.

AMIA ... Annual Symposium Proceedings. AMIA Symposium

|August 13, 2008

Summary

This summary is machine-generated.

Fast disease outbreak detection using an Algorithm Distribution Manager Service (ADMS) significantly reduces analysis time for long-running algorithms. Dynamic distribution on grid networks offers improved performance over single computers.

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Area of Science:

Computer Science
Public Health
Bioinformatics

Background:

Real-time biosurveillance relies on rapid data analysis for timely disease outbreak detection.
Grid technologies offer potential for distributed computing to accelerate complex analyses.

Purpose of the Study:

To describe and evaluate an Algorithm Distribution Manager Service (ADMS) for dynamic algorithm distribution.
To compare the performance of ADMS against single-computer analysis and static distribution.

Main Methods:

Developed an Algorithm Distribution Manager Service (ADMS) using grid technologies.
Partitioned and distributed detection algorithms dynamically across multiple computers (3 nodes).
Compared execution times on a single computer, a distributed grid network with static distribution, and a grid network with dynamic distribution.

Main Results:

Long-runtime algorithms completed approximately three times faster in a distributed environment compared to a single computer.
Short-runtime algorithms performed worse in the distributed environment.
Dynamic algorithm distribution outperformed static distribution.

Conclusions:

Dynamic algorithm partitioning and parallel processing show great potential for reducing lengthy analysis times in biosurveillance.
ADMS enables efficient distribution of algorithms from clients to remote grid computers.