Context-Aware Rate Limiting for Network Traffic Management
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Solution Overview
Problem
As the number of computing devices in data centers increases, the rising network traffic leads to decreased performance due to resource usage inefficiencies, necessitating techniques to enhance performance by managing network traffic effectively.
Innovation Solution
Implementing context-based rate limiting by a rate limiting engine that receives network events, determines priorities based on flow information and context such as user and application characteristics, and allocates packets to appropriate queues for optimized transmission.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If the number of computing devices in data centers increases, then processing capacity and functionality improve, but network traffic increases and performance decreases
Solution Approach 1:
The patent segments network traffic into different priority queues based on context information such as application characteristics, user characteristics, and flow information. This segmentation allows the system to handle different types of traffic differently, preventing high-priority traffic from being degraded by low-priority traffic, thus maintaining network performance while supporting increased computing devices
Solution Approach 2:
The system dynamically changes the parameter of packet transmission priority based on context information. By analyzing application characteristics, user characteristics, and flow information, the system adjusts priority levels in real-time, allowing optimal network performance adaptation as computing devices and traffic patterns increase
2Device complexity
If network traffic management is implemented without context information, then implementation complexity is reduced, but network performance optimization is insufficient
Solution Approach 1:
The system performs preliminary actions by collecting and analyzing context information (application characteristics, user characteristics, flow information) before making rate limiting decisions. This preliminary analysis enables more accurate priority assignment, improving network performance optimization without requiring complex real-time decision-making during packet processing
Data Source
AI summary
The disclosure provides an approach for rate limiting packets in a network. Embodiments include receiving, by a rate limiting engine running on a host machine, a network event related to a virtual computing instance running on the host machine, the network event comprising flow information about a network flow. Embodiments include receiving, by the rate limiting engine, context information corresponding to the network flow, wherein the context information comprises one or more of a user characteristic or an application characteristic. Embodiments include determining, by the rate limiting engine, a priority for the network flow by applying a rate limiting policy to the flow information and the context information. Embodiments include providing, by the rate limiting engine, the priority for the network flow to a multiplexer for use in rate limiting the network flow.