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Middleware system framework for distributed big data computing in a loose environment

A big data and distributed technology, applied in the direction of program control devices, etc., to achieve the effects of robust development, good programming simplicity and system robustness

Active Publication Date: 2016-12-28
NANJING NANZI INFORMATION TECH
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Problems solved by technology

[0004] The present invention proposes a middleware system framework for distributed big data computing in a loose environment. Its purpose is to adopt a solution of agent plus function manager plus function entity, and solve the problem through shared memory pipeline and accelerated local implementation. The operating efficiency of the existing framework, while maintaining and improving the consistency and effectiveness of the existing framework in terms of task scheduling and status monitoring through the agent plus function manager

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  • Middleware system framework for distributed big data computing in a loose environment
  • Middleware system framework for distributed big data computing in a loose environment

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Embodiment Construction

[0015] Control attached figure 1 , its structure includes agent module, function module and function management module, and the operation steps of each module are as follows:

[0016] Step 1: Connect the data source and format conversion function management module through the data source agent module, start the data source and format conversion task (function module), and the function management module simultaneously allocates the shared memory channel as the data source and format conversion task (function module) Output, related information (including shared memory interface information reflected in the proxy module);

[0017] Step 2: Connect the algorithm function management module through the algorithm agent module, start the algorithm analysis task (function module), and the function management module allocates the shared memory channel at the same time as the input of the algorithm analysis task (function module), and relevant information (including shared memory interfa...

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Abstract

The invention relates to a distributed big-data computation middleware system framework in a loose environment (hereinafter referred to as Rhizome). The Rhizome corresponds to a platform-as-a-service & infrastructure-as-a-service (PAAS&IASS) layer and is applicable to cloud big-data computation applications. The Rhizome comprises three frame bodies which include an agent module, a function module and a function management module. The Rhizome has the advantages that the problems that complex communication mechanisms can not be processed and the efficiency is low when the big-data computation applications are supported by common cloud distributed computation frameworks are solved, and meanwhile, an MoC, such as a data flow mode, can be used for displaying parallel modes for embodying and expanding the applications in the cloud computation frameworks; an adopted two-layer agent mode can support reliable and quantifiable client-side+cloud software development in cloud operating system environments, experimental assessments show that a Hadoop cloud video computation application is excellent in performance with the help of the Rhizome, and the programming simplicity, the hardware acceleration unit butt joint easiness and the system robustness which are high substantially are provided.

Description

technical field [0001] The present invention relates to a middleware system framework for distributed big data computing in a loose environment, corresponding to the PAAS&IASS layer in cloud computing, and used to build specialized high-efficiency big data computing applications (such as video processing applications in cloud computing environments), It can also be applied to heterogeneous MPSoC and multi-circuit board computer system software operating environments. Background technique [0002] Open-source cloud-based software such as Nimbus and Eucalyptus allows organizations to build their own cloud systems to facilitate the utilization of computing device resources. We can imagine that the acquisition of computing power is no longer necessary for users who need to perform centralized big data operations such as intelligent monitoring. is an obstacle. However, to perform such calculations two main prerequisites must be met: (i) simplicity of the programming model, bette...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06F9/44
Inventor 朱方孙建东
Owner NANJING NANZI INFORMATION TECH
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