Online Charging System Overload Rejection via CCR-U Segmentation
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Solution Overview
Problem
Conventional online charging systems face inefficiencies in handling overload situations by only rejecting initial interrogation signals, which becomes less effective as data services dominate, leading to potential revenue leakage and uneven prioritization between voice and data services.
Innovation Solution
The system selectively rejects Credit Control Request-Update (CCR-U) messages based on the presence and properties of Multiple Services Credit Control (MSCC) information, allowing for more aggressive rejection of data services over voice during overload, and implementing prioritization between different customer-facing services.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If the online charging system rejects only initial interrogation signals during overload, then the system maintains simplicity in overload handling, but this approach becomes less effective as data services dominate traffic, leading to potential revenue leakage
Solution Approach 1:
The patent segments the interrogation signals into different types (initial, intermediate, final) and applies different rejection strategies to each type based on their characteristics and impact on revenue. This allows the system to handle data services more effectively while maintaining manageable complexity through structured classification.
2Reliability
If the system rejects intermediate interrogation signals (CCR-U) during overload, then revenue leakage is reduced, but the system complexity increases due to need to evaluate MSCC information properties
Solution Approach 1:
The patent performs preliminary evaluation of the MSCC information properties in intermediate interrogation signals before making rejection decisions. By pre-assessing whether the signal contains only usage reporting or also includes service authorization requests, the system can make informed rejection decisions that protect revenue while managing complexity through structured assessment criteria.
3Reliability
If the system prioritizes voice services over data services during overload, then service quality for critical services is maintained, but the rejection of data service interrogations increases
Solution Approach 1:
The patent applies different quality levels and rejection thresholds to different service types based on their criticality. Voice services receive preferential treatment with lower rejection probabilities, while data services are subject to higher rejection rates during overload. This local differentiation of service quality ensures critical services maintain reliability while managing overall system load.
4Measurement precision
If the online charging system processes all interrogation signals during normal operation, then charging accuracy is maintained, but the system becomes vulnerable to overload conditions
Solution Approach 1:
The patent implements dynamic overload detection and adaptive rejection mechanisms that adjust the system's processing behavior based on current load conditions. During normal operation, the system maintains high charging accuracy by processing all signals. When overload is detected, the system dynamically transitions to selective rejection modes, preserving stability while maintaining acceptable charging accuracy through intelligent signal evaluation.
Data Source
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AI summary
Methods and systems for an online charging service to selectively rejecting Charge Control Requests (CCRs) which it receives and which are associated with charging for the provision of telecommunication services when the online charging system is in an overload state are described.