Bandwidth-Limited Device Update Classification
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Solution Overview
Problem
Cellular network providers face challenges in managing data updates for mobile devices, as heavy users consume more capacity than light users, leading to inefficiencies and potential cost disparities, where light users may subsidize heavy users or face increasing costs, making it undesirable for both groups.
Innovation Solution
A system and method that classify devices based on their usage, adjusting the frequency and granularity of updates to match available network capacity, allowing heavy users to exceed their allotment only when spare capacity is available, and utilizing alternate networks to reduce usage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If all devices receive full update information, then information completeness is improved, but network capacity consumption increases
Solution Approach 1:
The patent applies local quality by providing different levels of update information to different devices based on their usage patterns. Heavy users receive less detailed updates (lower granularity) while light users receive more comprehensive updates, matching the information quality to the specific needs and capacity consumption of each device group.
Solution Approach 2:
The system changes the parameter of information granularity based on device classification. By adjusting the level of detail in update information according to usage patterns, the system optimizes network capacity usage while maintaining sufficient information quality for each user group.
2Reliability
If heavy users are allowed to exceed their allotment, then service reliability is improved, but network capacity management deteriorates
Solution Approach 1:
The system dynamically adjusts the amount of update information provided to heavy users based on available network capacity. When spare capacity exists, heavy users can receive more information or exceed their allotment; when capacity is constrained, information is restricted. This dynamic approach maintains service reliability while optimizing overall network capacity efficiency.
Solution Approach 2:
The system monitors network capacity usage and provides feedback to adjust information delivery. By tracking capacity consumption and availability, the system can adaptively control update information distribution to heavy users, ensuring service continuity while preventing capacity exhaustion.
3Loss of energy
If light users subsidize heavy users, then system profitability is improved, but user satisfaction deteriorates
Solution Approach 1:
The system changes the pricing parameter from uniform pricing to usage-based pricing. By charging heavy users more based on their actual capacity consumption, the system eliminates the need for light users to subsidize heavy users, while maintaining system profitability through appropriate pricing of heavy user access.
Solution Approach 2:
The system dynamically adjusts pricing based on usage patterns and capacity consumption. Heavy users who consume more network capacity are charged higher fees, creating a fair pricing structure that reflects actual resource usage and eliminates cross-subsidization.
4Loss of information
If update frequency is increased, then information freshness is improved, but network capacity consumption increases
Solution Approach 1:
The system applies different update frequencies to different device groups based on their usage patterns. Light users receive more frequent and comprehensive updates, while heavy users receive less frequent updates with lower granularity, optimizing the balance between information freshness and network capacity consumption for each group.
Data Source
AI summary
A system and method detects an amount of data attributed to a device including reports sent to the device, and reduces the amount of data being used to provide reports to the device if the amount of data attributed to the device exceeds an amount assigned to the device. Data uploaded from the device is also minimized.