Dynamic Charging Rate Adjustment for Communication Networks
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing dynamic charging techniques in communication networks are inaccurate due to initial charge estimation based on instantaneous network load conditions, leading to over- or under-estimation, and result in inappropriate charging rates, especially during network congestion, and fail to account for service quality across multiple networks.
Innovation Solution
A method and system for dynamically determining a charging rate for communication sessions based on estimated quality of service and inter-network charging rates, with continuous monitoring and updating of charging rates during the session to ensure accurate billing commensurate with delivered service quality across multiple networks.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If initial charge estimation is based on instantaneous network load conditions, then charging rate can be determined quickly, but charging accuracy deteriorates due to over- or under-estimation
Solution Approach 1:
The charging rate is made dynamic rather than static, allowing it to change during the communication session based on evolving network conditions. The system transitions from a single instantaneous estimation to continuous adaptation, where the charging rate is updated periodically or upon significant network condition changes, resolving the contradiction between quick determination and accurate measurement.
Solution Approach 2:
The system implements feedback mechanisms where network load conditions and service quality metrics are continuously monitored and fed back to adjust the charging rate. This closed-loop approach allows the charging rate to be refined based on actual network behavior, improving accuracy while maintaining responsiveness to changing conditions.
2Measurement precision
If frequent load reporting by network elements is implemented, then charging accuracy improves through continuous monitoring, but processing and transmission overheads increase
Solution Approach 1:
Instead of continuous reporting, the system employs periodic reporting with configurable intervals. The reporting frequency is adjusted based on network conditions, session type, and operational requirements. This allows sufficient sampling for accurate charging while minimizing unnecessary overhead from overly frequent reports.
Solution Approach 2:
The reporting frequency is made dynamic rather than fixed, adapting to current network conditions and session characteristics. During stable conditions, reporting can be less frequent, while during volatile conditions, frequency increases automatically, optimizing the balance between accuracy and overhead.
3Loss of energy
If reporting frequency is decreased to reduce overhead, then processing and transmission costs decrease, but charging accuracy deteriorates due to missed conditions or events
Solution Approach 1:
The system uses feedback triggers based on significant changes in network conditions or service quality events. Rather than relying solely on time-based intervals, the system monitors for threshold breaches or significant events that warrant re-evaluation of the charging rate, ensuring accuracy is maintained without excessive reporting.
Solution Approach 2:
The system employs a hybrid approach where reporting is reduced (partial action) during stable conditions to minimize overhead, but increases (excessive action) when significant changes are detected to maintain accuracy. This flexible strategy optimizes the trade-off between overhead reduction and measurement precision.
4Productivity
If static charging policies are used, then charging determination is simple and fast, but revenue loss occurs during network congestion and service quality degradation
Solution Approach 1:
The charging system transitions from static policies to dynamic charging rates that adapt to network conditions in real-time. The system maintains simplicity through automated rate adjustment based on predefined parameters, while achieving revenue accuracy by responding to congestion and service quality changes without manual intervention.
Solution Approach 2:
The charging rate parameter is made variable rather than fixed, allowing it to change based on network load, service quality metrics, and session characteristics. This parameter flexibility enables the system to maintain both efficiency through automated adjustments and reliability through condition-responsive charging that prevents revenue loss during congestion.
Data Source
AI summary
A method for dynamic charging in a communication network is provided. The method may include dynamically determining a charging rate for the communication session upon initiation of a communication session, based on at least one of an estimated quality of service and a dynamically determined inter-network charging rate for the communication session. The method may further include initiating charging for the communication session based on the determined charging rate, monitoring at least an actual quality of service for the communication session with respect to the estimated quality of service for a duration of the communication session, and dynamically updating the determined charging rate based on the monitoring.