Dynamic Data Collection Rules for Network Load Management
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Solution Overview
Problem
Existing information collection systems do not consider overall network load when collecting data from edge apparatuses, leading to potential overload and operational issues.
Innovation Solution
An information collection system that includes a server apparatus and edge apparatuses, where collection rules are established to predict and manage the load by determining the content, frequency, and applicability of second information acquisition, thereby reducing the overall system load and preventing adverse effects like server or edge apparatus failure.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If data collection frequency is increased to improve monitoring accuracy, then information completeness is improved, but network load and system resource consumption increase
Solution Approach 1:
The patent implements dynamic data collection intervals where the frequency of data acquisition is adjusted based on current system conditions. When anomalies are detected, the collection frequency increases automatically; when systems are stable, frequency decreases. This dynamic adjustment resolves the contradiction by making information completeness adaptive rather than fixed, maintaining high monitoring accuracy when needed while reducing network load during normal operations.
Solution Approach 2:
The system changes the parameter of data collection interval based on system state. Different collection intervals are applied depending on whether anomalies are present, system load conditions, and data type priorities. This parameter change approach allows the system to optimize between information completeness and network load by selecting appropriate collection frequencies for different operational contexts.
2Reliability
If comprehensive data collection is performed to improve system monitoring, then monitoring accuracy is improved, but system complexity increases
Solution Approach 1:
The patent applies different data collection strategies to different edge apparatus and data types based on their specific requirements. Critical systems receive more frequent monitoring while non-critical systems use standard intervals. This local quality approach improves monitoring accuracy for important components without applying comprehensive high-frequency collection to all systems, thereby controlling overall system complexity.
Solution Approach 2:
The system segments data collection into different categories and applies tailored collection rules to each segment. Collection intervals, data types, and priorities are divided into multiple groups based on system criticality, data importance, and resource constraints. This segmentation allows comprehensive monitoring where needed while simplifying collection for less critical areas, resolving the contradiction between monitoring accuracy and system complexity.
3Speed
If data collection interval is shortened to improve response time, then response speed is improved, but resource consumption increases
Solution Approach 1:
The system implements periodic data collection with variable periods based on system state. Instead of continuous or fixed-interval collection, the system uses periodic actions where the period length adjusts dynamically. During normal operations, longer periods reduce resource consumption; when anomalies occur, periods shorten to improve response speed. This periodic action with adaptive timing resolves the contradiction between response speed and resource consumption.
Data Source
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AI summary
An information collection system (2000) includes a server apparatus (3000), a plurality of edge apparatuses (4000), and a collection rules storage unit (5000). The edge apparatus includes a first information generation unit (4020) that generates first information and a second information generation unit (4040) that generates second information. The collection rules storage unit (5000) stores collection rules so as to be associated with the edge apparatus (4000) and the first information that the server apparatus (3000) acquires from the edge apparatus (4000). The server apparatus (3000) includes a first information acquisition unit (3020) that acquires the first information from the edge apparatus (4000), a second information acquisition unit (3040) that acquires the second information from the edge apparatus (4000), and a collection rules acquisition unit (3060) that acquires collection rules from the collection rules storage unit (5000).