Charging System Predictive Notification Bundling
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Solution Overview
Problem
Existing telecommunications charging systems generate excessive signaling traffic by sending frequent updates between policy management and charging systems, particularly during peak periods like monthly billing cycles, leading to inefficient resource usage and performance degradation.
Innovation Solution
Implementing a method where the charging system predicts and bundles current and future subscriber state information, reducing the need for repeated communications by informing the policy management system of anticipated state changes in a single message, thereby minimizing signaling load and improving network performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the charging system sends frequent updates of subscriber state information to the policy management system, then the policy management system can make timely policy decisions, but the signaling traffic and network load increase significantly
Solution Approach 1:
The charging system predicts future subscriber state information in advance and includes it in the current notification message. This preliminary action allows the policy management system to prepare policy decisions beforehand, reducing the need for frequent follow-up updates and thereby decreasing signaling traffic while maintaining timely policy enforcement.
Solution Approach 2:
The notification message combines both current subscriber state information and predicted future state information into a single communication. This merging reduces the number of separate messages that would otherwise be transmitted, directly addressing the signaling traffic problem while ensuring the policy management system has comprehensive information for timely decision-making.
2Measurement precision
If the charging system sends individual updates for each subscriber state change, then accurate real-time information is provided, but the number of communication messages increases
Solution Approach 1:
The system performs preliminary prediction of future subscriber state changes and includes this information in advance. This allows the policy management system to anticipate state changes without waiting for individual update messages, maintaining accurate information while reducing the total number of communications required.
Solution Approach 2:
Instead of sending individual original update messages for each predicted state change, the system creates a consolidated notification that copies and bundles multiple state information updates into a single message. This approach maintains the accuracy of individual state information while dramatically reducing the number of separate communication events.
3Reliability
If the system processes and sends updates at peak times such as monthly billing cycles, then all balance state changes are captured, but the signaling load on charging and policy management systems increases
Solution Approach 1:
The charging system predicts future state changes in advance, including during peak periods like monthly billing cycles. By having this predicted information ready beforehand, the system can handle peak loads more efficiently without generating excessive signaling traffic, as the policy management system can process multiple predicted changes in a single notification rather than waiting for individual updates.
Solution Approach 2:
The notification message merges multiple balance state changes that would otherwise occur at the same peak time into a single consolidated communication. This merging approach ensures all balance state changes are captured and processed reliably while significantly reducing the signaling load on both charging and policy management systems during high-traffic periods.
Data Source
AI summary
A telecommunication network may include a policy management system and a charging system. The charging system may be configured to receive a request for subscriber state information relating to a subscriber from the policy management system, retrieve current subscriber state information from memory, determine future subscriber state information for the subscriber, generate a communication message that includes the current subscriber state information and the future subscriber state information, and send the generated communication message to the server computing device.


