Analytics-Triggered Subscriber Policies for Mobile Networks
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Solution Overview
Problem
Current mobile network systems face limitations in data collection granularity and subscriber-specific monitoring, which hampers efficient resource utilization and end-user experience due to limited capabilities of mobile network gateways.
Innovation Solution
A continuous feedback system that dynamically updates data collection criteria and subscriber policies based on aggregated data, utilizing a software-defined network (SDN) controller to adjust network topology and resource allocation, enabling more efficient data collection and processing of network traffic.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If mobile network gateway collects detailed and accurate monitoring data for each subscriber, then charging information accuracy is improved, but device complexity and data processing burden increase
Solution Approach 1:
The patent segments the monitoring system into two parts: the mobile network gateway that collects detailed subscriber-specific data, and a separate monitoring system that aggregates and analyzes this data. This segmentation allows the gateway to maintain measurement precision while reducing its processing burden and effective complexity by offloading aggregation functions.
Solution Approach 2:
The patent introduces a monitoring system as an intermediary between the mobile network gateway and the charging system. This intermediary aggregates detailed gateway data into summarized monitoring data, reducing the complexity of data processing while preserving charging information accuracy through selective data collection and aggregation.
2Measurement precision
If mobile network gateway collects granular network usage data, then data accuracy is improved, but loss of time for data processing increases
Solution Approach 1:
The monitoring system performs preliminary aggregation of detailed gateway data into summarized monitoring data before final analysis and charging decisions. This preliminary action reduces the volume of data requiring detailed processing, thereby reducing data processing time while maintaining accuracy through structured aggregation of granular usage information.
Solution Approach 2:
The system implements periodic data collection and aggregation cycles where the monitoring system regularly collects gateway data, aggregates it into monitoring data, and updates charging information. This periodic approach balances detailed measurement accuracy with reduced processing time by batching operations rather than continuous real-time processing of all granular data.
3Reliability
If mobile network gateway monitors all subscriber traffic in detail, then service quality monitoring is improved, but use of energy increases
Solution Approach 1:
The patent extracts the detailed data aggregation function from the mobile network gateway and places it in a separate monitoring system. The gateway continues to monitor all subscriber traffic in detail for service quality, but the energy-intensive aggregation and summarization operations are performed by the monitoring system, reducing gateway energy consumption while maintaining monitoring reliability.
4Reliability
If mobile network gateway collects comprehensive charging information, then revenue accuracy is improved, but device complexity increases
Solution Approach 1:
The system segments revenue assurance functions into two parts: the gateway collects comprehensive charging information and maintains service quality monitoring, while the monitoring system aggregates this data into monitoring data that ensures revenue accuracy. This segmentation reduces gateway complexity by offloading aggregation functions while preserving revenue accuracy through comprehensive data collection and systematic aggregation.
Data Source
AI summary
In general, techniques are described for providing a continuous feedback system that dynamically updates data collection criteria and subscriber policies based on aggregated subscriber-specific and network usage data. For example, a method includes applying one or more subscriber specific policy and charging control (PCC) rules to network traffic to collect network traffic data for a plurality of subscribers, aggregating the network traffic data, and determining, based on the aggregated traffic data, whether subscriber independent data collection criteria need to be updated. The method may also include, responsive to determining that the data collection criteria need to be updated: updating the data collection criteria, translating the updated data collection criteria from updated subscriber independent data collection criteria into updated subscriber specific PCC rules, and applying the updated subscriber specific policy and charging control rules to additional network traffic to collect additional network traffic data.