Cascading PID Controllers for Dynamic Network Traffic Routing
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Solution Overview
Problem
Existing network traffic management systems struggle to efficiently allocate traffic across multiple paths to optimize both cost and success rate, particularly in complex network environments with varying path qualities.
Innovation Solution
The implementation of a cascading controller system, where each path to a destination is associated with a proportional-integral-derivative (PID) controller, monitors success rates and adjusts traffic routing to optimize path utilization based on predefined criteria such as cost and success rate targets.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of energy
If traffic is routed through multiple paths with varying qualities, then cost efficiency improves, but routing complexity increases
Solution Approach 1:
The patent implements feedback mechanisms where controllers continuously monitor path success rates and adjust traffic routing decisions based on this feedback. Each controller receives performance data from its associated path and dynamically modifies routing to optimize cost efficiency while maintaining service quality, thereby managing routing complexity through intelligent adaptation rather than static complex configurations
Solution Approach 2:
The routing system is segmented into multiple independent controllers, each responsible for a specific path. This segmentation allows each controller to independently manage its path's traffic based on local conditions and success rates, simplifying the overall system architecture by distributing decision-making rather than requiring a single complex centralized routing logic
2Reliability
If traffic allocation is dynamically adjusted based on path quality, then success rate improves, but control complexity increases
Solution Approach 1:
The patent employs dynamic traffic allocation where controllers continuously adjust routing decisions based on real-time path quality metrics and success rates. This dynamic adaptation enables the system to respond to changing network conditions, improving reliability by directing traffic through optimal paths while using automated control algorithms to manage complexity rather than requiring manual intervention
Solution Approach 2:
Each controller operates autonomously to manage its associated path, making independent routing decisions based on monitored success rates and predefined policies. This self-service capability allows controllers to automatically adapt to path quality changes without external intervention, improving success rates through responsive local decision-making while reducing overall control complexity by distributing intelligence across multiple independent units
Data Source
AI summary
Aspects of the subject technology include receiving from a user device a request for obtaining data associated with the user device. The request is addressed to a destination device. Aspects also include determining with a first controller whether to transmit the request to the destination device via a first path. The determination is based on a first success rate of the first path. Aspects also include transmitting the request to the destination device via the first path in response to a determination to transmit the request to the destination device via the first path. Aspects also include determining, with a second controller, whether to transmit the request to the destination device via a second path, in response to a determination not to transmit the request via the first path. The determination is based on a second success rate of the second path.