Dynamic Usage Inequity Detection in Communications Networks
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Solution Overview
Problem
Conventional communications networks lack the ability to detect and remedy usage inequities, such as unauthorized device swapping or excessive data usage, after the service ordering phase, leading to potential costs for the network provider.
Innovation Solution
An architecture that includes an extraction component to retrieve subscriber information, a detection component to identify usage inequities, and a control service component to determine and apply suitable treatments, such as notifications or service restrictions, to mitigate usage inequities dynamically.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If the network provider allocates service plans based on devices identified during ordering, then service plan allocation is simplified, but the network cannot detect usage inequities after service is ordered
Solution Approach 1:
The system performs preliminary device identification and service plan allocation during the ordering phase, then continuously monitors usage patterns afterward to detect inequities. This preliminary action establishes a baseline that enables subsequent detection of unauthorized device swaps or usage violations.
Solution Approach 2:
The system implements continuous feedback loops where usage data is collected, analyzed against the provisioned service agreement, and used to trigger alerts or remediation actions when inequities are detected. This feedback mechanism transforms the static allocation process into a dynamic monitoring system.
2Reliability
If the network monitors subscriber usage continuously, then usage inequities can be detected, but system complexity increases
Solution Approach 1:
The monitoring function is extracted as a separate component that receives usage data from the network operations, analyzes it against service agreements, and generates alerts. This modular extraction reduces complexity by isolating the detection logic from the core network provisioning system.
Solution Approach 2:
An intermediary analysis layer is introduced between the raw usage data and the network provider, which filters and interprets usage patterns to identify inequities. This intermediary simplifies the overall system by handling the complex analysis task in a dedicated component rather than distributing complexity throughout the network.
3Adaptability or versatility
If service plans are made flexible with multiple features, then subscriber choices increase, but detecting appropriate usage becomes more difficult
Solution Approach 1:
The system applies different monitoring rules and thresholds to different features and usage types within service plans. Each feature (voice, data, messaging) has its own usage patterns and inequity detection criteria, allowing the system to handle plan versatility while maintaining precise detection capabilities for each service type.
Data Source
AI summary
An architecture that can dynamically detect and/or automatically remedy service usage inequities in a communications network is provided. For example, based upon a comparison of incoming call detail records (CDRs) to various subscriber information entities (e.g., service plan, blacklisted devices for the service plan, historic or current billing cycle usage, etc.), the architecture can identify when a usage inequity occurs or is likely to occur, substantially in real time.