Rules Engine for Wireless Prepaid Network Charging
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Solution Overview
Problem
Current prepaid wireless network systems lack the flexibility to offer a full range of mobile applications to users due to simplistic algorithms for calculating network usage and costs, limiting users to basic services like voice and MMS, and preventing them from adopting prepaid plans.
Innovation Solution
A method and system for monitoring network usage and calculating user charges based on predetermined rules, using a rules engine to match data packet parameters with charging rules, allowing for accurate tracking of prepaid quotas and enabling users to access a broader range of services.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a prepay scheme is implemented for wireless network access, then users can pay for talk time or data usage prior to using the network, but the network operators' simplistic algorithms for determining costs and network usage constrain users to basic services only
Solution Approach 1:
The patent segments the charging system into multiple independent charging rules, each handling specific service types (voice, data, MMS, etc.). The rules engine evaluates packets against these segmented rules sequentially, allowing complex prepaid charging logic to be broken down into manageable, service-specific segments that can be independently configured and maintained.
Solution Approach 2:
The patent introduces a rules engine as an intermediary component between the prepaid charging system and the network services. This rules engine acts as a mediator that intelligently evaluates data packets against multiple charging rules, determining whether to apply prepaid charging or allow free access based on service type, thereby enabling full service range without requiring complex algorithms throughout the entire system.
2Productivity
If users are charged based on simplified algorithms, then real-time cost calculation is achieved, but the full range of mobile applications such as voice, MMS, VoIP, applications, and web browsing are not available
Solution Approach 1:
The charging system is segmented into discrete charging rules, each corresponding to a specific service type or application category. This segmentation allows the system to quickly identify and apply the appropriate charging rule without performing complex overall calculations, maintaining real-time processing speed while supporting diverse applications.
Solution Approach 2:
The rules engine dynamically evaluates each data packet against the current set of charging rules, adapting the charging decision based on the specific service type and user's prepaid balance. This dynamic evaluation enables the system to handle various applications in real-time without requiring static, overly simplistic algorithms.
3Reliability
If prepaid limits are enforced strictly, then users cannot exceed their prepaid quota, but this prevents users from accessing services they have not yet paid for
Solution Approach 1:
The system implements feedback mechanisms where the rules engine continuously monitors the user's prepaid balance and service usage. When a user approaches their quota limit, the system can provide warnings or transition to different charging rules (such as throttling or requiring top-up), thereby maintaining reliable quota enforcement while preserving ease of operation through gradual transitions rather than abrupt service denial.
Solution Approach 2:
The charging enforcement is made dynamic through the rules engine, which can adjust the strictness of quota enforcement based on service type, user profile, and current balance. This allows the system to maintain reliability for critical services while providing flexibility and ease of access for non-critical services, adapting the enforcement level to operational context.
Data Source
AI summary
This disclosure relates to methods and systems for monitoring network usage according to predetermined rules and calculating user charges based on the network usage. The described technique includes receiving a data packet, extracting parameters from the data packet and determining whether the extracted parameters match at least one rule in a rules engine. Charges for the data packet are calculated based on the matched rules. The data packet is forwarded on to its destination.