Large-scale monitoring video stream converging method based on stream-oriented computation

A technology for monitoring video and streaming computing, applied in TV, CCTV systems, electrical components, etc., can solve problems such as video stream concentration, and achieve the effect of improving overall efficiency and universal applicability

Active Publication Date: 2016-04-13
SHANGHAI JUNESH INFORMATION TECH CO LTD
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

[0003] However, the receiving position of the video stream in the cluster is random, and it is very likely that the video stream is concentrated on a small number of machines to start

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  • Large-scale monitoring video stream converging method based on stream-oriented computation
  • Large-scale monitoring video stream converging method based on stream-oriented computation
  • Large-scale monitoring video stream converging method based on stream-oriented computation

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Embodiment Construction

[0047] The technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the embodiments of the present invention. Apparently, the described embodiments are only some of the embodiments of the present invention, not all of them. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts belong to the protection scope of the present invention.

[0048] In the embodiment of the present invention, a method for converging large-scale surveillance video streams based on streaming computing mainly solves the following two problems: first, interacting with external video sources to ensure that large-scale streaming data can be stably imported to the analysis system; second, the choice of storage location, to ensure that the storage location of streaming data can meet the requirements of building a good distributed collectio...

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Abstract

The invention discloses a large-scale monitoring video stream converging method based on stream-oriented computation. The method comprises the following four steps: I, acquiring information about all cameras, and performing ranking according to importance degrees, required central processing unit (CPU) resources and Internet protocol (IP) addresses; II, acquiring information about Workers, and performing ranking according to CPU computing capabilities and IP addresses; III, selecting a properly-identified Worker computing container to serve as a startup position of a receiver according to a computing resource chain table; and IV, estimating resource computing capabilities of selected Workers. According to the method, the complexity in inputting data sources and the computing capabilities of the Workers are considered fully, and the video stream startup position is computed reasonably, so that data are executed locally as much as possible; the CPU utilization ratio of a system is increased; and the real-time computing capability of the system is enhanced. The method has a high practical value and a good application prospect in the technical field of parallel real-time processing of massive video data.

Description

technical field [0001] The invention relates to the technical field of computer processing, in particular to a method for converging large-scale surveillance video streams based on streaming computing. Background technique [0002] The "pooling" of large-scale video sources, that is, the reception of video stream data from video sources, is a precursor to parallel processing. This process needs to address two important issues. First, the interaction with external video sources ensures that large-scale streaming data can be stably imported into the analysis system; second, the choice of storage location ensures that the storage location of streaming data can meet the requirements of building a good distributed collection . A well-distributed collection can reduce a lot of unnecessary data transfers for parallel processing. [0003] However, the receiving positions of the video streams in the cluster are random, and it is very likely that the video streams are concentrated ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): H04N7/18H04N21/647
CPCH04N7/181H04N21/64723H04N21/64769
Inventor 阳海华
Owner SHANGHAI JUNESH INFORMATION TECH CO LTD
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