Rule-driven data transmission method

Abstract

The invention discloses a rule-driven data transmission method. The method comprises the steps that (1) constraint condition decomposition is carried out on historical distribution tasks of each candidate data transmission network to obtain the characteristic attribute of each historical task of the corresponding network; (2) a common characteristic attribute of the historical tasks of each network is determined, a network business rule is built according to each common characteristic attribute, and the business rules of all the networks are built into a business rule chain; (3) the characteristic attribute of each task to be distributed is extracted from the constraint condition of the task to be distributed; (4) characteristic matching is carried out on the characteristic attribute of the task and the business rule chain, and if a matched business rule exists, data transmission is carried out on the task by the adoption of the network corresponding to the business rule; if not, matching is carried out on the constraint condition of the task and characteristic attributes of data, channels and nodes, and data transmission is carried out on the task by selecting one candidate network. According to the rule-driven data transmission method, optimization scheduling can be formed on the basis that the constraint conditions of the tasks are matched with the business rules.

Description

technical field [0001] The invention belongs to the technical field of information resource transmission (Resource Dispatch), and relates to a rule-driven data transmission method. Background technique [0002] Taking meteorological data transmission as an example, at present, the global communication system of the World Meteorological Organization, the national meteorological communication system and the industrial meteorological communication network all adopt a variety of communication methods to meet the operational transmission requirements of large-scale, high time-efficiency and large data volume. The basic model is to realize rapid broadcasting and distribution of information based on satellite communication and upload data in areas that are difficult to cover with cable, to realize big data exchange between backbone nodes and high-quality audio and video information interaction such as video conference based on ground dedicated lines, and to realize information publi...

AI Technical Summary

Problems solved by technology

Existing methods are relatively coarse-grained, and cannot refine the attribute characteristics of distribution tasks in a fine-grained manner, and it is difficult to automatically realize the decomposition, combination and matching of features

The main problems include: 1) lack of feature classification system for distribution tasks, fine-grained division of various features of distribution tasks; 2) lack of interpretation mechanism for constraints, feature attributes and business rules represented by distribution tasks

3) Lack of a complete rule-based task scheduling and transmission process

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