Packet Filtering Group Trees for Accurate 5G QoS Classification
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Solution Overview
Problem
Existing packet filtering technologies in communication networks face challenges due to heavy processing and memory constraints, particularly in handling large numbers of packet filters and complex traffic classification, leading to incorrect classification and resource overburden, especially in 5G networks with features like ultra-reliable low-latency communication (URLLC) and network slicing.
Innovation Solution
Implement techniques such as indicating maximum packet filter support, prioritizing packet filtering rules, adapting filter support based on hardware load, and optimizing traffic descriptor identification to manage resource constraints and ensure accurate packet classification.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the number of packet filters is increased to handle complex traffic classification in 5G networks, then traffic classification accuracy is improved, but processing overhead and memory consumption increase
Solution Approach 1:
The patent segments packet filters into multiple groups organized in a filter group tree structure, where each group contains filters with similar characteristics. This segmentation allows the system to manage and process filters in smaller, organized units rather than as a single large set, reducing processing overhead while maintaining classification accuracy.
Solution Approach 2:
The patent performs preliminary actions by pre-processing packet filters to identify and extract common characteristics before actual packet filtering occurs. The filter group tree is built in advance, organizing filters by shared attributes, so that during runtime, packets can be classified more efficiently by traversing the pre-organized structure rather than checking all filters individually.
2Reliability
If comprehensive packet filtering is implemented to ensure accurate QoS flow routing, then service quality is improved, but resource consumption increases
Solution Approach 1:
The patent applies local quality by assigning different processing depths and scrutiny levels to different groups of packet filters based on their importance and characteristics. Critical QoS-related filters are examined more thoroughly, while less critical filters use simplified matching, ensuring high routing accuracy for important traffic while conserving resources on less sensitive flows.
Solution Approach 2:
The patent implements partial action by selectively applying comprehensive filtering only where necessary for QoS guarantees, rather than uniformly processing all packets with maximum scrutiny. The system identifies which filter groups require detailed examination and applies appropriate processing levels, avoiding excessive resource consumption on packets that don't require full filtering depth.
3Speed
If packet filter processing is optimized to reduce latency, then processing speed is improved, but classification accuracy may deteriorate
Solution Approach 1:
The patent performs preliminary organization of packet filters into a structured tree before actual packet processing. This pre-processing creates an optimized data structure that enables faster traversal during runtime without sacrificing classification accuracy, as the logical relationships between filters are preserved in the tree structure.
Solution Approach 2:
The patent segments the filter processing into hierarchical levels within the filter group tree, allowing packets to be classified through progressive refinement rather than exhaustive checking. This segmentation enables the system to quickly eliminate non-matching filter groups at higher levels and only perform detailed classification on relevant subsets, improving speed while maintaining accuracy.
Data Source
AI summary
The present application relates to devices and components including apparatus, systems, and methods for user equipments and network components performing or assisting in packet filtering operations.