Dynamic Quota Allocation Based on Consumption Speed
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Solution Overview
Problem
Current online charging systems face inefficiencies in quota allocation, leading to signaling overload, balance starvation, and unexpected debits from monetary balances due to fixed quota sizes, which result in increased operational costs and customer dissatisfaction.
Innovation Solution
An apparatus and method that dynamically calculate quota consumption speed using a Time-Rolling window algorithm, allowing for adaptive quota size determination based on consumption history, available allowance, and network load, to optimize quota allocation and reduce signaling overload.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If fixed quota sizes are allocated to subscribers, then quota allocation is simple and fast, but signaling overload occurs and balance starvation happens
Solution Approach 1:
The patent applies dynamics by transitioning from fixed quota sizes to dynamic quota allocation. The system calculates quota consumption speed based on historical consumption patterns and uses this to determine adaptive quota sizes. This allows the quota allocation system to respond to changing subscriber behavior patterns, preventing both over-allocation (which causes signaling overload) and under-allocation (which causes balance starvation).
Solution Approach 2:
The patent implements feedback mechanisms by monitoring actual quota consumption and using this information to adjust future quota allocations. The system calculates quota consumption speed based on historical data and feeds this back into the quota determination process. This closed-loop approach enables the system to learn from past behavior and optimize future allocations, reducing unnecessary signaling while ensuring adequate balance allocation.
2Loss of energy
If large quota sizes are granted to reduce signaling transactions, then operational costs decrease, but balance starvation occurs and customer experience deteriorates
Solution Approach 1:
The patent applies parameter changes by adjusting quota sizes based on calculated consumption speeds. Instead of using fixed large quotas that waste resources, the system dynamically modifies the quota parameter according to actual consumption patterns. This allows the system to grant larger quotas when consumption speed indicates high usage likelihood, while reducing quotas when consumption is low, thereby preventing balance starvation while optimizing operational costs.
3Measurement precision
If quota allocation is based on consumption speed and historical data, then quota allocation accuracy improves, but system complexity increases
Solution Approach 1:
The patent applies preliminary action by pre-calculating and storing consumption speed metrics based on historical quota usage patterns. The system performs this calculation in advance during normal operation, creating a lookup table or cache of consumption speeds. When a new quota allocation is needed, the system simply retrieves the relevant consumption speed data rather than performing complex real-time analysis, thus achieving high accuracy while limiting the increase in system complexity to manageable levels.
Data Source
AI summary
It is provided a method, comprising monitoring if a request for granting a requested quota for a subscriber is received; calculating a quota consumption speed based on a consumption of a previous quota granted to the subscriber and a duration during which the previous quota is consumed; determining a determined quota size based on the quota consumption speed; granting a granted quota to the subscriber in response to the received request, wherein the granted quota has the determined quota size.