Dynamic Network Filter Thresholds for Load Optimization
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Solution Overview
Problem
Existing network systems face challenges in ensuring that client devices receive only subscribed levels of data transmission services, leading to potential overloading of network components and inefficient resource allocation, as filters may either restrict or exceed subscribed bandwidth and services.
Innovation Solution
Implementing a system that measures network load and client device utilization in real-time, generating optimization instructions to redirect resources from oversubscribed clients to undersubscribed ones, and re-routing data flows to alleviate overloaded components, while allowing oversubscribed clients to receive additional services when capacity permits.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If filters are implemented to prevent client devices from receiving greater data transmission services than subscribed, then client devices receive only subscribed bandwidth, but network components may be overloaded when filters drop data during bursts
Solution Approach 1:
The filter thresholds are made dynamic rather than static. The system continuously monitors network component load and adjusts filter thresholds in real-time. When network components are lightly loaded, higher thresholds allow more data transmission. When components approach capacity, thresholds are lowered to prevent overload. This dynamic adjustment resolves the contradiction by adapting bandwidth enforcement to actual network conditions rather than using fixed limits.
Solution Approach 2:
The system implements feedback loops that monitor network component utilization metrics and use this information to adjust filter thresholds. The feedback mechanism ensures that bandwidth enforcement adapts to real-time network conditions, allowing the system to maintain both subscription compliance and optimal data transmission by continuously balancing these competing requirements.
2Productivity
If filters are provisioned to permit maximum bandwidth at each backend network device, then client devices can receive subscribed bandwidth, but other client devices cannot receive subscribed bandwidth when one client uses excessive bandwidth
Solution Approach 1:
The system monitors actual bandwidth consumption of each client device and uses this feedback to dynamically adjust filter thresholds. When a client device consumes more than its subscribed bandwidth, the system detects this through feedback mechanisms and adjusts thresholds to enforce fair allocation. This ensures that no single client can monopolize network capacity while others remain underserved.
Solution Approach 2:
The system changes filter threshold parameters based on real-time monitoring of client device behavior and network conditions. By dynamically adjusting these parameters rather than using fixed values, the system can respond to bandwidth abuse patterns and ensure fair resource distribution across all client devices while maintaining high overall productivity.
3Reliability
If filters are implemented to enforce subscription limits, then bandwidth is controlled, but network components may be overloaded from hardware perspective even when clients receive subscribed services
Solution Approach 1:
The system dynamically adjusts filter thresholds based on real-time monitoring of both client bandwidth consumption and network component load. When network components are lightly loaded, the system permits higher data transmission even for clients at or slightly above subscription levels. When components approach capacity, thresholds are adjusted to ensure compliance. This dynamic approach resolves the contradiction by making enforcement adaptive to actual system state rather than rigid.
Solution Approach 2:
The system implements comprehensive feedback mechanisms that monitor both client-side bandwidth consumption and network component utilization. This dual feedback allows the system to distinguish between legitimate high-demand clients and bandwidth abusers, and to adjust filters accordingly while preventing component overload. The feedback loops ensure subscription compliance without unnecessary restriction of legitimate traffic.
Data Source
AI summary
A server may receive flow information from multiple network devices. The flow information may include information regarding multiple data flows received by the multiple network devices and destined for a client device. The server may determine generate an optimization instruction, based on flow information, to re-route one or more of the plurality of data flows or to apply filters to the one or more of the plurality of data flows; provide the optimization instruction to cause one or more of the multiple network devices to re-route one or more of the multiple data flows or to apply filters to the one or more data flows to alleviate overloaded network components or to re-route network resources to or from the client device; receive updated flow information after receiving the flow information; generate an updated optimization instruction based on the updated flow information; and provide the updated optimization instruction.