Containerization-based traffic algorithm standardized packaging method

A packaging method and algorithm technology, applied in the direction of instruments, calculations, program control devices, etc., can solve the problems of not providing external call interfaces, high development costs, parameters, and interface confusion, etc., to meet the needs of rapid deployment and facilitate query and deployment , the effect of reducing the amount of information transmitted

Pending Publication Date: 2020-11-03
SHENZHEN URBAN TRANSPORT PLANNING CENT
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0014] (1) Patent Application No. 201710958539.1, "Big Data Platform for Public Transportation Travel Services", uses a single platform's customized development algorithm to analyze and process data, and the development cost is high;
[0015] (2) Patent Application No. 201610587725.4, "A Smart City Traffic Management Platform", uses different systems to independently set up on the platform, and the algorithm exists independently in each system, and the information and algorithms of different systems are processed through the terminal server of the platform Transmission, high transmission cost;
[0016] (3) Patent application No. 201510518249.6, "Docker-based large-scale computing experiment meth

Method used

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  • Containerization-based traffic algorithm standardized packaging method
  • Containerization-based traffic algorithm standardized packaging method
  • Containerization-based traffic algorithm standardized packaging method

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specific Embodiment approach 1

[0063] Specific implementation mode one, combining Figure 1-Figure 5 Explain this implementation method: the current algorithm uses the Flask framework to implement basic interface services. Flask is a web framework of python. The biggest feature is that it is light and easy to use, allowing developers to be freely and flexibly compatible with the applications to be developed;

[0064] In this embodiment, the combination of gunicorn and gevent is selected to load and run the Flask application, so the Dockerfile needs to be set to execute the gunicorn configuration file.

[0065] All algorithms need to be encapsulated into a RESTful interface and packaged into a Docker image, and hosted on the transportation big data platform for unified operation and management;

[0066] As attached to the manual figure 1 and figure 2 as shown, figure 1 A step-by-step diagram for algorithm image packaging and deployment, figure 2 The overall architecture diagram encapsulated by the algo...

specific Embodiment approach 2

[0074] Specific embodiment two, in a containerized traffic algorithm standardization encapsulation method based on the present embodiment, the specific steps of developing the algorithm calling interface of the HTTP protocol according to the RESTful architecture using Python's Flask are:

[0075] Step S21. Configure the traffic algorithm call interface development tool;

[0076] Step S22. Complete the installation of the traffic algorithm call interface framework and the generation of the algorithm call interface.

[0077] Among them, combined with the manual attached image 3 Explanation The specific steps for configuring the traffic algorithm call interface development tool in step S21 are:

[0078] Step S211. install plug-ins gunicorn and gevent;

[0079] Step S212. configuration file;

[0080] Write the configuration file of gunicorn (file name gunicorn.conf.py), set internal parameters of gunicorn, including process parameter worker, working mode parameter worker_class...

specific Embodiment approach 3

[0101] Specific implementation mode 3, in a standardized encapsulation method for traffic algorithms based on containerization in this implementation mode,

[0102] Mirror name specification:

[0103] The image name (Repository) refers to the part of the full name of the image before the colon (:), and the part after the colon (:) is the image tag (tag), which is used to distinguish the image version. For example, a mirror named my-app:3.1.4, my-app is the Repository part of the mirror.

[0104] Mirror names are separated by forward slashes ( / ), and the part before ' / ' is an optional host name in DNS format. The host name must comply with the DNS rules, but must not contain the underscore '_' character, and the host name can be a port number in the format of 8080.

[0105] The mirror name naming convention is: "host name / mirror warehouse name / subject / algorithm name", the algorithm name adopts the "subject-predicate" structure, all words are lowercase letters, and the words a...

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Abstract

The invention discloses a containerization-based traffic algorithm standardized packaging method, and belongs to the technical field of intelligent traffic data processing. The method comprises the following steps: S1, completing core content development of a traffic algorithm; s2, developing an algorithm RESTful interface of an HTTP (Hyper Text Transport Protocol) by adopting a Flask of python; s3, performing Docker mirror image manufacturing on the algorithm and the running environment; s4, deploying the mirror image to an algorithm warehouse of a traffic big data platform; and S5, applyingfor an interface service on the traffic big data platform, successfully calling an algorithm interface after data is input, and returning an output result. The packaged traffic algorithms are uniformly stored in the big data platform and do not need to be respectively stored in the platform subsystems, a user can call the traffic algorithms from the uniform algorithm pool, the containerized traffic algorithm mirror image starting avoids parameters and interface disorder of traffic algorithm operation, a container is released after the traffic algorithms are used up, and the information transmission quantity is reduced.

Description

technical field [0001] The invention relates to an independent packaging method for a traffic algorithm, belonging to the technical field of intelligent traffic data processing. Background technique [0002] In recent years, the field of intelligent transportation has developed rapidly relying on the development of big data technology. In order to serve the monitoring, management and judgment of intelligent transportation, many transportation big data platforms have been born. These traffic big data platforms will not only collect multi-party and multi-source traffic data such as signal control, traffic flow monitoring, and personnel travel from a certain area, but also collect cross-field data such as economy and environment. In order to empower comprehensive traffic governance, in addition to collecting and statistical data, it is also necessary to use these data for analysis and calculation. Therefore, the big data platform will also deploy traffic system algorithms, suc...

Claims

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Application Information

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IPC IPC(8): G06F8/61G06F9/455
CPCG06F8/63G06F9/45504G06F9/45558G06F2009/45591
Inventor 张晓春林涛丘建栋钟莉谭章智潘嘉杰傅恺延
Owner SHENZHEN URBAN TRANSPORT PLANNING CENT
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