Intelligent Network Ingress Limits for Per-Flow Congestion Control
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Solution Overview
Problem
Existing network architectures face challenges in scalability, versatility, and efficiency due to increasing network load and diverse traffic types, with conventional congestion control mechanisms being slow and ineffective, especially in large or heavily loaded networks.
Innovation Solution
A data-driven intelligent networking system with ingress port injection limits that maintains state information of individual packet flows, uses flow-specific input queues, and acknowledges packets at the egress point to enable dynamic flow control and congestion management, allowing each switch to obtain state information and apply injection limits.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If conventional congestion control mechanisms are used, then network architecture is simple, but flow control speed and effectiveness are slow
Solution Approach 1:
The patent segments the network into flow-specific input queues at each switch, allowing independent congestion control for each flow. This segmentation enables fast, effective flow control by managing packets on a per-flow basis rather than using conventional shared buffers, directly addressing the speed requirement while maintaining architectural clarity through modular queue management.
2Reliability
If per-flow state information is maintained, then flow control effectiveness improves, but device complexity increases
Solution Approach 1:
The patent implements per-flow state information through dedicated flow-specific input queues at each switch. Each queue maintains its own state independently, allowing effective flow control without requiring complex centralized state management. The segmentation approach distributes state information locally at each switch, improving reliability while keeping the complexity manageable through decentralized queue management.
3Productivity
If injection limits are applied at ingress ports, then network capacity is enhanced, but device complexity increases
Solution Approach 1:
The patent applies injection limits at ingress ports before packets enter the network fabric. By pre-limiting the injection rate at the source, the system prevents congestion before it occurs, enhancing network capacity utilization. The preliminary action approach at ingress ports simplifies downstream congestion management while improving overall network productivity through proactive rate control.
4Reliability
If fast flow control is implemented, then congestion is prevented, but network versatility may be reduced
Solution Approach 1:
The patent segments the network into flow-specific queues that can independently manage congestion for different traffic types. This segmentation enables fast flow control for each flow while maintaining network versatility, as each flow can be controlled according to its specific characteristics without affecting other flows. The modular approach allows diverse traffic patterns to be handled efficiently through independent queue management.
Data Source
AI summary
Data-driven intelligent networking systems and methods are provided. The system can accommodate dynamic traffic while applying injection limits to different traffic classes at an ingress edge port. The system can maintain state information of individual packet flows, which can be set up or released dynamically based on injected data. Each flow can be provided with a flow-specific input queue upon arriving at a switch. Packets of a respective flow can be acknowledged after reaching the egress point of the network, and the acknowledgement packets can be sent back to the ingress point of the flow along the same data path. Furthermore, an edge switch can dynamically allocate the ingress port bandwidth among the traffic classes that are active at a given moment.