Mobile Device Data Allocation System for Shared Plan Management
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Solution Overview
Problem
Shared data plans for mobile devices often lead to exceeding allocated data amounts due to unpredictable data usage among group members, as users are unaware of each other's data needs, especially during high-usage periods, resulting in potential overage fees.
Innovation Solution
A mobile device data allocation system that analyzes metadata and usage history to predict increased data usage and regulates data transmission by prioritizing devices and throttling data exchange to prevent exceeding the allocated data limit, using a shared-account device module and cloud computing environment to manage data usage across multiple devices.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of energy
If a shared data plan is used among multiple mobile devices, then cost efficiency is improved by consolidating data usage, but data overage occurs because individual usage cannot be tracked or controlled
Solution Approach 1:
The system continuously monitors data usage across all shared devices and provides real-time feedback to users about their consumption. The server tracks total usage against the shared plan limit and notifies users when approaching the threshold, enabling them to adjust behavior and avoid overage fees.
Solution Approach 2:
A server acts as an intermediary between the mobile devices and the data network. It intercepts and monitors data requests from multiple devices, tracks cumulative usage, and enforces the shared plan limits by blocking or throttling traffic when the collective usage approaches the allocated threshold.
2Reliability
If data usage is monitored and controlled in real-time across shared devices, then data overage is prevented, but system complexity increases due to tracking multiple devices
Solution Approach 1:
The system consolidates monitoring of multiple devices through a single server that tracks cumulative usage across all shared devices. Instead of each device independently tracking its own usage, the server aggregates data from all devices and enforces the collective limit, simplifying the overall system architecture.
Solution Approach 2:
Each mobile device includes a module that automatically reports its data usage to the server and receives control signals in return. The system operates autonomously without requiring manual intervention from users to track or report usage, as the devices self-report and the server automatically enforces limits.
3Reliability
If predictive analysis is used to anticipate data usage spikes, then data overage can be prevented in advance, but computational resources are consumed for analyzing usage patterns
Solution Approach 1:
The system performs preliminary analysis of usage patterns to predict future data consumption spikes. By identifying trends and anomalies in historical data, the system can proactively notify users or automatically throttle usage before the predicted spike occurs, preventing overage rather than reacting after the fact.
Solution Approach 2:
The predictive analysis focuses on key indicators and patterns rather than analyzing every single data packet. The system monitors aggregate usage trends and significant deviations from normal patterns, applying computational resources selectively to identify likely overage scenarios without exhaustive analysis of all traffic.
Data Source
AI summary
A mobile device data allocation system includes a plurality of mobile devices that exchange data with a data service provider via a communication network. The data exchanged by each mobile device during a time period defines a total amount of exchanged data. An electronic shared-account device module is configured to determine a maximum amount of data at which the mobile devices are authorized to exchange during the time period. The shared-account device module further generates a control signal that regulates data exchange of the at least one mobile device in response to determining an upcoming event indicating the total amount of exchanged data will exceed the maximum amount of data.