Dynamic Credit Update for Adaptive Packet Sampling
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Solution Overview
Problem
Existing time-based packet sampling mechanisms face challenges in maintaining optimal sampling rates due to static credit values, leading to oversampling for small packets and undersampling for larger packets, especially when bandwidth varies.
Innovation Solution
A dynamic credit update system calculates credit values based on the link rate and average packet size of each data source, tied to the rate of access control list statistics collection, using a combination of hardware components like FPGAs and software modules to manage packet sampling rates dynamically.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If static credit values are used in time-based packet sampling, then the sampling mechanism is simple to implement, but the sampling accuracy deteriorates under varying bandwidth conditions
Solution Approach 1:
The patent implements dynamic credit values that automatically adjust based on actual network traffic conditions. The sampling rate is continuously adapted by monitoring packet arrival rates and adjusting credit allocations accordingly, transforming the static sampling mechanism into a dynamic one that maintains accuracy under varying bandwidth conditions.
Solution Approach 2:
The system incorporates feedback mechanisms where sampling statistics and traffic patterns are continuously monitored and fed back to adjust credit values. This closed-loop control ensures that the sampling rate responds to actual network conditions, improving measurement precision while maintaining implementation feasibility through structured feedback processing.
2Measurement precision
If sampling rate is increased to capture more traffic patterns, then measurement completeness improves, but network resource consumption increases
Solution Approach 1:
The patent dynamically changes sampling parameters including credit values and sampling rates based on traffic characteristics. By adjusting these parameters according to actual network conditions, the system achieves measurement completeness only when necessary, thereby optimizing network resource consumption while maintaining adequate measurement precision.
Solution Approach 2:
The system applies partial sampling action by using credit-based mechanisms to sample only the necessary portion of traffic. Instead of uniformly sampling all packets, the system selectively samples based on credit availability and traffic patterns, achieving adequate measurement completeness with reduced resource consumption.
3Measurement precision
If dynamic credit updates are implemented to adapt to varying traffic conditions, then sampling accuracy improves, but system complexity increases
Solution Approach 1:
The patent implements self-service mechanisms where the sampling system automatically adjusts its own credit values and sampling rates based on monitored traffic conditions. This self-adjusting capability improves sampling accuracy without requiring complex external control systems, as the system serves itself by making real-time adaptations based on embedded monitoring and decision logic.
Solution Approach 2:
The system performs preliminary calculations and preparations for credit updates by pre-establishing update intervals and thresholds. This preliminary action allows dynamic credit updates to be implemented systematically, reducing the complexity of real-time decision-making while maintaining sampling accuracy through pre-planned adjustment strategies.
Data Source
AI summary
A method is provided in one example embodiment and includes receiving a packet flow from a data source at a network element; determining a control value for controlling a sample rate for the packet flow; and recalculating the control value based on a number of packets received and a number of sampled packets. In more particular embodiments, the method can include assigning a particular identifier to a particular packet of the packet flow; generating an input access control list for the data source; and matching the particular identifier to an output port of the network element. In yet other embodiments, the method can include generating a copy of a particular packet of the packet flow; and forwarding the copy of the particular packet to an output access control list based on an assigned quality of service (QoS) group.