Method execution on a distributed image processing back-end

Niederl, Franz; Goller, A.

doi:10.1109/empdp.1998.647205

Cited by 7 publications

(2 citation statements)

References 2 publications

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“…see work in [30] Intelligent subtasking Automatic subtasking of a bigger coarsegrained task into fine-grained subtasks that are available in form of services/functions. This area is still in infancy, however preliminary level work on automatic subtasking is presented in [31] VI. BRIEF DISCUSSION OF OUR RESEARCH WORK IN DISTRIBUTED IMAGE PROCESSING…”

Section: Research Work In Distributed Image Processingmentioning

confidence: 99%

Analytical study of parallel and distributed image processing

Prajapati

Vij²

2011

2011 International Conference on Image Information Processing

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The available literature on parallel and distributed image processing is scattered and not organized for use to beginners. Thus, there is a need of concise understanding of parallel and distributed image processing area. In this paper, we present analysis of parallel and distributed image processing with comprehensive details, so that it becomes very useful to beginners and to those who are new to parallel or distributed image processing field. We present the outcome of our study of parallel and distributed image processing with emphasis on mechanisms, tools/technology/API used, application domains, and ongoing research work. We examine the research issues in parallel and distributed image processing. We also identify some future research directions for distributed image processing. This study provides concise understanding of the parallel and distributed image processing area to the beginners.

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Section: Research Work In Distributed Image Processingmentioning

confidence: 99%

Analytical study of parallel and distributed image processing

Prajapati

Vij²

2011

2011 International Conference on Image Information Processing

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“…Many other efforts with similar goals to our's exist. The Distributed Image Processing Shell (DIPS) 13 and its successor Concurrent and Distributed Image Processing 14–16 used NetSolve 17 to create a distributed image processing system. These two approaches are most similar to our study and provide several significant contributions that should be considered when conceiving distributed image processing systems.…”

Section: Related Workmentioning

confidence: 99%

Distributed image processing over an adaptive Campus Grid

Caton

Rana

Batchelor

2008

Concurrency and Computation

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A system implemented in MATLAB is described, which may be deployed over a Campus Grid utilizing the Condor job management system. Our approach can re-distribute jobs as node availability changes. The architecture of the system, its components, and their deployment across the Cardiff University Campus Grid (consisting of 2500 machines) are presented. Challenges in image processing applications that can be deployed over such infrastructure are presented, along with performance results that demonstrate the use of our system alongside a standard Condor deployment, demonstrating a significant increase in throughput using our approach ‡ .

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