Paper
19 September 1997 Distribution of image processing applications on a heterogeneous workstation network: modeling, load balancing, and experimental results
Daniel Hernandez-Sosa, Jorge Cabrera-Gamez
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Abstract
This work analyzes the computation distribution in applications generated by a multilevel knowledge-based system for image processing called SVEX. This distribution has been carried out on a heterogeneous workstation network, trying to take advantage of the availability and frequent infra- utilization of this computational resource. The parallelization is based on message-passing tool parallel virtual machine (PVM). Firstly SVEX and its computational scheme are described, detailing the structure of the first level (the pixel processor). Then different distribution paradigms are studied, selecting for its implementation the parallelism based on the data. Considering this alterative, the research addresses two fundamental problems: analysis of basic load-balancing schemes and obtaining a model for predicting parallelization behavior as new machines are added to the computational network. The results produced in a series of experiments permit the comparison of load-balancing schemes and the validation of the proposed model. The experiments include the processing of both static images and sequences.
© (1997) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Daniel Hernandez-Sosa and Jorge Cabrera-Gamez "Distribution of image processing applications on a heterogeneous workstation network: modeling, load balancing, and experimental results", Proc. SPIE 3166, Parallel and Distributed Methods for Image Processing, (19 September 1997); https://doi.org/10.1117/12.279615
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Cited by 1 scholarly publication.
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KEYWORDS
Image processing

Image segmentation

RGB color model

Analytical research

Data modeling

Data processing

Sensors

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