Statistical Analysis for Communication Network Capacity Management
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Solution Overview
Problem
Abusive usage of prepaid mobile phones by a few customers can significantly impact network service providers' communication network capacity, leading to the need for costly infrastructure expansions to manage limited capacity.
Innovation Solution
A system utilizing a processor, data store, and analysis component to calculate mean and standard deviation of communication metrics for customers, identifying potentially abusive users and sending messages to encourage proper usage, offering assistance, and warning of service termination if abuse continues.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If the service provider purchases expensive equipment to expand network capacity, then the network capacity is improved, but the cost increases
Solution Approach 1:
The system performs preliminary identification of abusive customers through statistical analysis of communication metrics before network capacity is severely impacted. By detecting patterns of abusive usage in advance and sending warning messages to these customers, the system prevents future capacity consumption by abusive users, thereby avoiding the need for costly capacity expansion
Solution Approach 2:
The system establishes a feedback loop by continuously monitoring communication metrics, comparing them against statistical norms (mean and standard deviation), and sending messages to customers when abnormal patterns are detected. This feedback mechanism enables real-time correction of abusive behavior, preventing the accumulation of capacity waste that would require expensive infrastructure upgrades
2Quantity of substance
If the service provider monitors and manages abusive usage, then the network capacity is preserved, but the complexity of the system increases
Solution Approach 1:
The system enables self-service monitoring by automatically collecting communication metrics from the network, performing statistical analysis to identify abusive patterns, and sending messages to customers without human intervention. The automated identification process uses mean and standard deviation calculations to flag suspicious usage patterns, and the system autonomously manages the entire workflow from detection to customer notification
Solution Approach 2:
The system replaces manual monitoring and analysis with automated computational methods. Instead of human operators reviewing usage patterns, the system uses processor-based statistical analysis (mean and standard deviation calculations) to automatically identify abusive customers. This substitution of mechanical/computational processes for manual operations reduces operational complexity while maintaining effective capacity management
Data Source
AI summary
A system is provided for managing communication network capacity. The system includes a processor, a data store, an analysis component, and a message component. The data store stores information associated with communication metrics for customers. The analysis component, when executed by the processor, determines a mean and a standard deviation for the communication metrics based on the stored information. The analysis component also determines whether the stored information associated with communication metrics for one of the customers is a predefined number of the standard deviation from the mean for more than a predefined number of days. The message component, when executed by the processor, sends a message to the one of the customers in response to a determination that stored information associated with the communication metrics for the one of the customers is the predefined number of the standard deviation from the mean for more than the predefined number of days.