Dynamic CDR Generation for Mobile Billing Systems
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Solution Overview
Problem
Existing systems for generating call detail records (CDRs) in communication networks face inefficiencies, as they generate records at fixed intervals, leading to inaccurate usage reporting for subscribers approaching their data limits and overwhelming processing and billing systems, due to inadequate frequency adjustments based on individual usage patterns.
Innovation Solution
The system dynamically adjusts CDR generation parameters based on a mobile device subscriber's network usage, increasing frequency when nearing usage limits and decreasing it when far from limits, using a billing system module and Policy Charging and Enforcement Function (PCEF) to optimize CDR generation, taking into account usage percentages, number of users, past behavior, and billing cycle phases.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If fixed interval CDR generation is used for all subscribers, then processing systems are not overwhelmed, but usage reporting accuracy deteriorates for subscribers approaching data limits
Solution Approach 1:
The patent implements dynamic CDR generation intervals that adjust based on each subscriber's real-time network usage relative to their data plan limits. When a subscriber approaches their data limit (e.g., 80-90% threshold), the system automatically reduces the CDR generation interval to provide more frequent usage updates. Conversely, when usage is well below limits, the interval increases to reduce processing load. This dynamic adjustment resolves the contradiction by making the system adaptive to individual subscriber conditions rather than applying a fixed interval to all users.
Solution Approach 2:
The system changes the temporal parameter (CDR generation interval) based on the state parameter (network usage percentage). By monitoring usage thresholds and adjusting the CDR generation frequency accordingly, the system optimizes both measurement precision for approaching limits and processing efficiency for low-usage periods. This parameter change strategy allows the same system to serve multiple operational states effectively.
2Measurement precision
If CDR generation interval is reduced to improve usage monitoring, then usage reporting accuracy improves, but processing system burden increases
Solution Approach 1:
The patent applies different CDR generation qualities (intervals) to different subscriber groups based on their local conditions. Instead of uniformly reducing intervals for all subscribers, the system identifies specific subscribers approaching their data limits and applies shorter intervals only to those users. This localized approach ensures high monitoring accuracy is applied where needed while maintaining efficient processing for the majority of users who are not approaching their limits, thus resolving the contradiction between monitoring accuracy and CDR volume.
Solution Approach 2:
The system dynamically changes the CDR generation parameter (interval duration) based on the subscriber's usage state. When usage exceeds a predetermined threshold (e.g., 80% of data limit), the interval parameter is reduced to improve monitoring. When usage is below the threshold, the interval parameter is increased to reduce CDR volume. This conditional parameter change resolves the contradiction by making the system responsive to actual monitoring needs.
3Device complexity
If fixed interval CDR generation is used, then processing is simplified, but timeliness of usage notifications deteriorates for approaching limits
Solution Approach 1:
The system transitions from static fixed-interval processing to dynamic condition-based processing. By continuously monitoring usage patterns and automatically adjusting CDR generation timing, the system maintains processing simplicity through automation while dramatically improving notification timeliness. When a subscriber approaches their data limit, the system dynamically shifts to a shorter interval regime, ensuring timely notifications without requiring complex manual intervention or predetermined scheduling.
Solution Approach 2:
The system implements a feedback loop where CDR generation decisions are based on real-time usage information. The monitoring mechanism detects when usage approaches predetermined thresholds and automatically adjusts the CDR generation interval in response. This feedback-driven approach maintains processing simplicity through rule-based automation while ensuring timely notifications are generated precisely when needed, resolving the contradiction between processing simplicity and notification timeliness.
Data Source
AI summary
A system and method for generating Call Detail Records (CDR) to optimize network usage notifications to a mobile device subscriber. The system and method can include a billing system module that determines CDR generation parameters for the mobile device subscriber based on the mobile device subscriber's network usage, including increasing CDR generation when the mobile device subscriber's network usage relative to a predetermined quota is high and/or decreasing CDR generation when the mobile device subscriber's network usage relative to the predetermined quota is low. The CDR generation parameters can be applied to control CDR generation for the mobile device subscriber.