Adaptive Mobile Bandwidth Thresholds for Wireless Data Throttling
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Solution Overview
Problem
Mobile devices exceeding their allotted bandwidth usage on wireless telecommunication networks face throttling, which current systems manage inefficiently, often leading to unnecessary disruptions and increased costs due to bandwidth limitations.
Innovation Solution
A recommender system that dynamically adjusts bandwidth thresholds for various data usage types (roaming, home, voice over IP, international voice over IP, roaming voice over IP, international data, and tethering) based on usage patterns and user feedback, allowing for temporary or permanent increases in thresholds when necessary.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If bandwidth throttling is applied when mobile devices exceed their allotted bandwidth usage, then network congestion is controlled and operational costs are reduced, but user experience deteriorates and unnecessary disruptions occur
Solution Approach 1:
The system dynamically adjusts bandwidth thresholds based on real-time usage patterns, device type, and network conditions rather than applying static limits. This allows the network to adapt to changing demands and prevent unnecessary throttling while maintaining control during peak congestion periods
Solution Approach 2:
The system continuously monitors bandwidth usage patterns and feeds this information back to adjust thresholds and throttling decisions. By analyzing historical and real-time data, the system learns from past behavior and optimizes bandwidth allocation to balance network efficiency with user experience
2Device complexity
If static bandwidth thresholds are applied to all devices, then network management is simplified, but bandwidth utilization efficiency decreases and user-specific needs are not met
Solution Approach 1:
The system segments bandwidth management into device-specific profiles with customized thresholds based on device type, usage patterns, and user preferences. This segmentation allows tailored bandwidth allocation without requiring complex manual configuration for each device
Solution Approach 2:
The system automatically generates device profiles and adjusts bandwidth thresholds based on monitored usage patterns without requiring manual intervention. The self-learning mechanism analyzes usage data and autonomously optimizes bandwidth allocation, reducing management complexity while improving efficiency
3Loss of energy
If bandwidth throttling is applied early to prevent exceeding limits, then operational costs are reduced, but legitimate high-usage scenarios are disrupted
Solution Approach 1:
The system changes bandwidth threshold parameters dynamically based on the specific usage scenario, device type, and historical patterns. Instead of applying uniform early throttling, the system adjusts parameters to accommodate legitimate high-usage scenarios while still controlling costs through intelligent allocation
Data Source
AI summary
The system obtains multiple thresholds for multiple bandwidth usage types associated with a UE. The threshold indicates an amount of bandwidth available to the UE over a predetermined period. Each threshold corresponds to a bandwidth usage type. The multiple thresholds include: roaming data, home data, voice over IP, international voice over IP, roaming voice over IP, international data, and tethering data threshold. The system obtains multiple bandwidth usage patterns of the UE, where each bandwidth usage pattern corresponds to a threshold. The system iterates over each bandwidth usage to determine whether the UE has exceeded or is likely to exceed the threshold within the predetermined period. Upon determining that a bandwidth usage pattern has exceeded or is likely to exceed the threshold within the predetermined period, the system determines an increase to the threshold. The system sends an indication of the increase to the threshold to the UE.