Multi-rule Encoding for Network Packet Classification
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Solution Overview
Problem
Current network systems face inefficiencies in processing and securing multiple network protocol layers (L3-L7) simultaneously, particularly in packet classification for advanced internet services like routing, access control, and intrusion detection, which requires efficient rule encoding and decoding to manage storage and runtime performance.
Innovation Solution
A method and system for encoding key matching rules using a rule encoding engine that builds a multi-rule by storing a multi-rule header and dimension data, enabling efficient storage and decoding through techniques like interleaving values, disabling unnecessary dimension matching, and prioritizing rules, thereby reducing memory usage and processing time.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If sequential encoding methods are used for packet classification rules, then rule processing can be performed in a straightforward manner, but memory usage and processing time increase significantly
Solution Approach 1:
The patent merges multiple individual rule encodings into a single multi-rule encoding structure. Instead of encoding each rule separately with its own header and data fields, the invention combines N rules into one multi-rule that shares common header information (such as priority, match type, and action fields), thereby reducing redundant storage and improving processing efficiency.
Solution Approach 2:
The multi-rule encoding structure serves multiple functions simultaneously: it stores and processes multiple rules, maintains priority ordering, supports different match types (exact match, prefix match, range match), and enables efficient memory access patterns. This universal structure replaces multiple specialized single-rule encodings.
2Reliability
If individual rule headers are stored for each key matching rule, then rule specificity is maintained, but storage efficiency decreases by up to 75%
Solution Approach 1:
The patent combines the header information of multiple rules into a shared multi-rule header that is common to all N rules in the group. This header contains fields such as priority, match type indicators, and action specifications that are either identical or hierarchically related across the rules, eliminating redundant storage while preserving rule-specific matching accuracy through the dimension data portion.
Data Source
AI summary
A multi-rule approach for encoding rules grouped in a rule chunk is provided. The approach includes a multi-rule with a multi-rule header representing headers of the rules and, in some cases, dimensional data representing dimensional data of the rules. The approach further includes disabling dimension matching of always matching dimensions, responding to an always match rule with a match response without matching, interleaving minimum/maximum values in a range field, interleaving value/mask values in a mask field, and for a given rule of rule chunk, encoding a priority field at the end of dimension data stored for the rule in the multi-rule. Advantageously, this approach provides efficient storage of rules and enables the efficient comparison of rules to keys.