Network Time Series Visualization with Adaptive Data Subsetting
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Solution Overview
Problem
Network administrators face challenges in efficiently identifying network issues due to the inefficiencies in current methods for analyzing large data sets over time, which often result in misleading data and performance bottlenecks, especially when visualizing network data on mobile devices.
Innovation Solution
A system that dynamically adjusts time intervals and constructs queries to retrieve a subset of data values, preserving data quality, thereby reducing network calls and bandwidth usage, allowing for real-time monitoring and visualization of network performance without performance constraints on mobile devices.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If all data values are retrieved and displayed, then complete data information is provided, but network bandwidth is excessively consumed and mobile device performance is saturated
Solution Approach 1:
The system extracts and displays only the most relevant data points from the complete dataset. By identifying and retrieving key data points that represent the essential information while filtering out redundant data, the system maintains data completeness for decision-making purposes while significantly reducing network bandwidth consumption and mobile device processing load.
2Measurement precision
If high resolution data is displayed, then detailed information is provided, but unwanted or misleading data is also shown
Solution Approach 1:
The system applies different quality levels to different parts of the data visualization. High-resolution detailed data is displayed for critical time periods or anomaly points where precision is essential, while lower-resolution aggregated data is used for normal operational periods. This selective application of data quality ensures detailed information is provided where needed without displaying unwanted or misleading data throughout the entire dataset.
3Productivity
If more data points are plotted, then comprehensive analysis is enabled, but mobile device networking capacity is exceeded
Solution Approach 1:
The system segments the complete dataset into multiple batches or time-based groups, retrieving and displaying data in manageable portions rather than loading all data points simultaneously. This segmentation enables comprehensive analysis capability by allowing users to navigate through different time periods or data categories while keeping each individual data retrieval operation within the mobile device's networking capacity limits.
Data Source
AI summary
A method that includes receiving, from a client device, a pre-selected period of time, and determining whether multiple data values corresponding to the pre-selected period of time exceeds a threshold permitted by a network service request is provided. The method includes determining an interval at which the network service request is made based on the pre-selected period of time, and constructing a query that requests the data values with a constraint, wherein the constraint reduces the data values corresponding to the pre-selected period of time to a subset of data values that preserve a data quality. The method also includes making the network service request using the query and displaying results received in a response to the network service request.