Communication Data Collection Templates for Unified Filtering
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Solution Overview
Problem
Existing data collection methods in communication systems are complex, leading to missing or repeated data collection, and incur high transmission and storage costs due to the lack of unified data collection and processing, especially with the rise of massive data volumes and new data types such as sensing and AI models.
Innovation Solution
Implementing a data orchestration or control apparatus that provides a match table and action set to a first communication apparatus for unified data collection and filtering, ensuring accurate and high-quality data processing by avoiding redundancy and reducing data volume and costs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional data collection method is used, then data can be collected from network elements, but the operations become complex and missing or repeated data collection is likely to occur
Solution Approach 1:
The data collection system is segmented into distinct functional components: a data collection template definition module that defines collection rules, a data collection execution module that executes collection based on templates, and a data processing module that handles the collected data. This segmentation allows each component to perform its specific function independently, reducing overall operational complexity while maintaining collection accuracy through template-based standardization.
Solution Approach 2:
The system changes the parameters of data collection by introducing standardized collection templates that define specific attributes and formats. Instead of ad-hoc collection operations, the system uses parameterized templates that specify what data to collect, how to collect it, and how to process it, thereby simplifying operations and ensuring consistent, accurate data collection across different network elements.
2Loss of information
If massive data is transmitted and stored, then complete data information is preserved, but transmission and storage costs become relatively high
Solution Approach 1:
The system extracts only the necessary data elements from the potentially massive data streams by using targeted collection templates. Each template specifies precise extraction criteria (what data to collect, from where, and in what format), ensuring that only relevant information is transmitted and stored, thereby reducing costs while maintaining information completeness for the intended purposes.
Solution Approach 2:
The system performs preliminary data processing and filtering at the collection stage by applying templates that pre-define what data should be collected and how it should be formatted. This preliminary action prevents unnecessary data from being transmitted and stored in the first place, reducing transmission and storage costs while ensuring that only high-quality, relevant data is retained.
3Reliability
If unified data collection and processing is implemented, then data collection accuracy is improved, but system complexity increases
Solution Approach 1:
The system implements universality by creating a multi-functional data collection framework where templates serve multiple purposes: defining collection criteria, specifying data formats, guiding execution, and directing processing. This universal template approach handles various data types and collection scenarios through a single standardized mechanism, improving accuracy while managing complexity through consolidation rather than proliferation of specialized components.
Data Source
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AI summary
Disclosed are a data collection and processing method and an apparatus, which relate to the field of communication technologies and are capable of unifying data collection and/or filtering and processing operations and reducing data transmission and storage costs. The method includes: obtaining a match table and an action set that are associated with a first communication apparatus; and sending, to the first communication apparatus, the match table and the action set that are associated with the first communication apparatus, where the first communication apparatus is an initial data agent apparatus in a data transmission process, the match table indicates collection and/or filtering processing on data obtained from a data source, the match table includes identification information of the first communication apparatus and a service identifier, and the action set indicates one or more actions associated with the service identifier.