Subscriber Data Aggregation at Network Interception Edge
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Solution Overview
Problem
Current network monitoring systems face challenges in efficiently aggregating subscriber-perspective data due to high bandwidth, storage, and computing resource requirements, especially with increasing network traffic, and lack effective methods for handling encrypted transport protocols.
Innovation Solution
A computer-implemented method and system that intercepts live network traffic packets, selects and aggregates content data from specific subscriber end devices, and outputs results at the point of interception, using an interception device with a processor and memory to inspect, decrypt, and process packets, reducing the need for raw data transmission and storage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If large quantities of raw subscriber data are transferred and stored at a remote location for aggregation and analytics, then complete subscriber perspective data can be obtained for network performance measurement and business analytics, but bandwidth consumption, storage requirements, and computing resources are excessively large
Solution Approach 1:
The patent applies preliminary action by performing aggregation and analytics operations at the edge device (proximal to data sources) before transferring data to the remote location. This preprocessing reduces the volume of data that needs to be transmitted and stored remotely, while still preserving complete subscriber perspective data for analysis. The edge device consolidates raw data from multiple sources into aggregated results, eliminating the need to transfer and store all raw data at the remote location.
2Reliability
If conventional network monitoring systems collect and process all raw network traffic data centrally, then comprehensive network analysis can be performed, but the computational load and resource requirements increase significantly with growing network traffic
Solution Approach 1:
The patent applies segmentation by dividing the data processing function into two parts: edge devices perform initial aggregation and analytics on local data, while the remote location performs higher-level analysis on the aggregated results. This segmentation reduces the computational load at any single location and distributes processing responsibilities, maintaining analysis accuracy while reducing overall device complexity and resource requirements.
3Extent of automation
If subscriber data is aggregated and analytics are performed at a remote location from intercepted traffic, then centralized control and analysis are achieved, but the amount of data transmission and storage requirements become unsustainable
Solution Approach 1:
The patent applies preliminary action by implementing automated aggregation and analytics at the edge device before data leaves the local network. This preliminary processing maintains centralized control capabilities while dramatically reducing the energy consumption associated with data transmission and storage at remote locations. The edge device performs energy-intensive processing locally, eliminating the need to transmit large volumes of raw data over the network.
Data Source
AI summary
A system and method to aggregate subscriber-perspective data from live data packets of network traffic. The method includes inspecting live packets of network traffic exchanged with a plurality of subscriber end devices. Network traffic exchanged with a subscriber end device can include network traffic exchanged with a different subscriber end device or with an application server. The packet inspection is performed at a location of interception of the live packets, each subscriber end device being an end device correlated with a subscriber. The method further includes selecting, at the location, content data of the inspected packets that correspond to packets exchanged with a selected subscriber end device of the plurality of subscriber end devices, aggregating, at the location, the content data selected, wherein the content data has not been previously aggregated, and outputting, at the location, results of the aggregation.