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PARALLEL IMAGE DATABASE PROCESSING WITH MAPREDUCE AND PERFORMANCE EVALUATION IN PSEUDO DISTRIBUTED MODE

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Publicado en:International Journal of Electronic Commerce Studies vol. 3, no. 2 (2012), p. 211
Autor principal: Yamamoto, Muneto
Otros Autores: Kaneko, Kunihiko
Publicado:
Academy of Taiwan Information Systems Research
Materias:
Programming languages
Performance enhancement
Metadata
Performance evaluation
Image databases
Databases
Cloud computing
Cameras
Data processing
Video data
Image processing
Camcorders
Distributed processing
Electronic commerce
Acceso en línea:Citation/Abstract
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Resumen:With recent improvements in camera performance and the spread of low-priced and lightweight video cameras, a large amount of video data is generated, and stored in database form. At the same time, there are limits on what can be done to improve the performance of single computers to make them able to process large-scale information, such as in video analysis. Therefore, an important research topic is how to perform parallel distributed processing of a video database by using the computational resource in a cloud environment. At present, the Apache Hadoop distribution for open-source cloud computing is available from MapReduce1. In the present study, we report our results on an evaluation of performance, which remains a problem for video processing in distributed environments, and on parallel experiments using MapReduce on Hadoop2.
ISSN:2073-9729
DOI:10.7903/ijecs.l092
Fuente:ABI/INFORM Global