DPI Sampling for Wireless Traffic Characterization
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Solution Overview
Problem
Wireless communication networks face challenges in managing and evaluating data traffic efficiently to handle growing demands for high-bandwidth applications, requiring advanced methods to sample and characterize traffic flows without consuming unnecessary resources.
Innovation Solution
A deep packet inspection (DPI) system that samples data flows based on traffic characteristics, such as application type and quality of service, to determine an appropriate sampling frequency, thereby optimizing resource usage and maintaining accurate traffic characterization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If deep packet inspection is performed on all traffic flows to accurately characterize applications, then measurement precision is improved, but use of energy and device complexity increase
Solution Approach 1:
The patent applies partial action by performing deep packet inspection only on a sampled subset of traffic flows rather than all flows. The inspection node selects a sampling rate based on traffic characteristics, inspecting only the necessary portion of traffic to achieve accurate application characterization while reducing overall energy consumption and processing load.
Solution Approach 2:
The patent changes the parameter of inspection intensity by dynamically adjusting the sampling rate based on traffic characteristics. For different application types and traffic patterns, the system modifies the proportion of packets subjected to deep inspection, thereby optimizing the balance between measurement precision and energy consumption.
2Measurement precision
If deep packet inspection is performed on all traffic flows to accurately characterize applications, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The patent reduces device complexity by performing deep packet inspection only on a sampled subset of traffic flows. The inspection node implements a sampling mechanism that selects a manageable portion of traffic for inspection, avoiding the need to process and analyze every single packet through the complex deep inspection pipeline.
Solution Approach 2:
The system dynamically adjusts the inspection sampling rate based on traffic characteristics and inspection node capacity. By changing this parameter, the system can scale the level of deep packet inspection to match available resources, thereby managing device complexity while maintaining adequate measurement precision.
3Measurement precision
If sampling rate is increased to improve traffic evaluation accuracy, then measurement precision is improved, but loss of energy increases
Solution Approach 1:
The patent optimizes the sampling rate parameter based on traffic characteristics such as application type, packet size, and flow duration. By dynamically adjusting this parameter, the system achieves the minimum necessary sampling rate to maintain measurement precision while minimizing energy consumption associated with packet inspection and processing.
Data Source
AI summary
An inspection node receives an event to begin monitoring a traffic flow where the event comprises a flow identifier associated with the traffic flow. The inspection node receives the traffic flow where the traffic flow comprises a plurality of packets and begins inspecting the plurality of the packets to obtain an application identifier. Based upon the flow identifier and the application identifier, the inspection node performs a sampling process on the traffic flow. After determining the end of the traffic flow, the inspection node terminates the sampling process.