文章基本信息

标题：Large Scale Image Processing in Real-Time Environments with Kafka
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作者：Yoon-Ki Kim ; Chang-Sung Jeong
期刊名称：Computer Science & Information Technology
电子版ISSN：2231-5403
出版年度：2017
卷号：7
期号：1
页码：207-215
DOI：10.5121/csit.2017.70120
出版社：Academy & Industry Research Collaboration Center (AIRCC)
摘要：Recently, real-time image data generated is increasing not only in resolution but also inamount. This large-scale image originates from a large number of camera channels. There is away to use GPU for high-speed processing of images, but it cannot be done efficiently by usingsingle GPU for large-scale image processing. In this paper, we provide a new method forconstructing a distributed environment using open source called Apache Kafka for real-timeprocessing of large-scale images. This method provides an opportunity to gather related datainto single node for high-speed processing using GPGPU or Xeon-Phi processing.
关键词：Real Time Image Processing; Distributed Processing; Real-Time Processing; Apache Kafka