Satellite Network Congestion Throttling via Dynamic Bandwidth Allocation
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Solution Overview
Problem
Current methods for managing bandwidth in satellite-based networks fail to utilize available free bandwidth efficiently, leading to wasted resources and degraded performance, especially during peak hours, as they do not dynamically distribute bandwidth to subscribers based on real-time usage and congestion levels.
Innovation Solution
A congestion-based throttling system that continuously monitors network capacity and usage patterns to dynamically adjust data service speeds for subscribers, prioritizing active users during non-peak hours and applying adaptive speed throttling based on historical congestion levels and machine learning algorithms to reduce waste and enhance overall network efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If uniform throughput speed increase is applied to all subscribers who have exceeded their data allowance, then the throughput speed for these subscribers is improved, but the network becomes overloaded during peak hours causing degraded speeds for all subscribers
Solution Approach 1:
The patent implements dynamic throttling that adjusts throughput speeds in real-time based on current network conditions. Instead of uniform speed increases, the system continuously monitors network utilization and dynamically adjusts subscriber speeds - increasing speeds when bandwidth is available and reducing speeds when congestion occurs. This dynamic approach resolves the contradiction by making throughput speed flexible rather than fixed, allowing the system to improve speeds without causing overload.
Solution Approach 2:
The system employs feedback mechanisms where network performance metrics are continuously monitored and fed back to the throttling algorithm. The algorithm uses this feedback to adjust throttling levels - when network performance degrades due to overload, the system automatically reduces speeds to restore balance. This closed-loop feedback system resolves the contradiction by creating a self-regulating mechanism that prevents overload while maximizing throughput when possible.
2Ease of operation
If throughput speed is throttled based on data usage limits, then fair allocation according to subscription is achieved, but available free bandwidth is wasted and not leveraged to advantage
Solution Approach 1:
The patent transforms static throttling based on fixed data allowances into dynamic throttling that responds to real-time network conditions. When free bandwidth is available, the system dynamically increases speeds for subscribers who have exceeded their allowances, allowing them to utilize unused capacity. This resolves the contradiction by making the allocation system adaptive - maintaining fairness through subscription-based baseline allocation while dynamically distributing available free bandwidth to maximize utilization without compromising fair allocation principles.
Solution Approach 2:
The system changes the parameters of throttling from fixed data usage limits to dynamic parameters that include current network utilization, available bandwidth, and subscriber priority levels. By introducing these additional parameters, the system can adjust speeds based on both fair allocation requirements and available capacity, resolving the contradiction between fair allocation and bandwidth utilization by considering multiple factors simultaneously rather than relying solely on fixed data limits.
3Productivity
If free bandwidth is distributed to subscribers during non-peak hours, then customer satisfaction and throughput are improved, but network monitoring and dynamic adjustment complexity increases
Solution Approach 1:
The patent implements a universal throttling algorithm that handles multiple functions within a single system component. The same algorithm manages both peak and non-peak hours, handles multiple subscriber types, and responds to various network conditions using a unified approach. This multi-functionality resolves the contradiction by consolidating complexity into a single versatile system rather than requiring separate mechanisms for different scenarios, thereby improving throughput without proportionally increasing overall system complexity.
Solution Approach 2:
The throttling system operates autonomously using automated algorithms that monitor network conditions and adjust speeds without human intervention. The system self-regulates by detecting congestion patterns and automatically applying appropriate throttling levels, eliminating the need for manual configuration and reducing operational complexity. This self-service capability resolves the contradiction by allowing the system to handle complex dynamic adjustments automatically, improving throughput while keeping the operational burden manageable through automation rather than manual processes.
Data Source
Figure 1~2A
Figure 2B~3
Figure 4~5
AI summary
A system and method for reducing waste of a network resource is disclosed. The method including: providing a group of active subscribers; determining an underutilization level of the network resource for an upcoming allocation interval; calculating a throttle and a resource weight for the group of active subscribers to decrease the underutilization level; allocating the network resource based on the throttle and the resource weight; and adjusting, based on a feedback underutilization level, the throttle and the resource weight. In some embodiments, the throttle is based on congestion metrics including measuring available channel capacity, a latency, a queue depth, a count of subscribers in an outroute channel or the like. In some embodiments, the active subscribers may include under subscribers, over subscribers and premium subscribers, wherein each of the over subscribers have exceeded a respective network resource usage allowance for a respective subscription interval.