Rule Compiled Data Structure Incremental Update Heuristics
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Solution Overview
Problem
Current packet classification methods in network devices face inefficiencies in handling incremental updates to rule sets, leading to performance degradation and complexity in maintaining balanced decision trees, especially in high-traffic networks where real-time updates are necessary without disrupting active search processes.
Innovation Solution
The implementation of a Rule Compiled Data Structure (RCDS) that allows for atomic updates, including adding, deleting, or modifying rules, while maintaining a balanced decision tree structure through incremental updates, using a compiler module and housekeeping tree to manage changes and adaptively recompile sections based on heuristic criteria.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If incremental updates are performed on the rule set during active search processes, then the system can adapt to changing network conditions in real-time, but the decision tree structure may become unbalanced and performance may degrade
Solution Approach 1:
The rule set is divided into multiple sections or partitions within the decision tree structure. When incremental updates occur, only the affected sections are modified while other sections remain intact and balanced, preventing global performance degradation. This segmentation allows localized updates without disrupting the overall tree balance.
Solution Approach 2:
The system performs preliminary actions by pre-allocating update buffers and maintaining shadow copies of decision tree sections. Before applying incremental updates, the system prepares the necessary structural adjustments in advance, ensuring that the decision tree remains balanced during and after updates, thus maintaining classification performance consistency.
2Stability of the object's composition
If the decision tree is recompiled frequently to maintain balance after incremental updates, then tree balance is preserved, but computational overhead increases
Solution Approach 1:
Instead of recompiling the entire decision tree after every incremental update, the system performs partial recompilation only on the specific sections that became unbalanced. This partial action approach maintains tree balance where needed while avoiding the excessive computational overhead of full tree recompilation, thus resolving the contradiction between stability and complexity.
3Reliability
If atomic updates are implemented for the rule set, then consistency is maintained during updates, but the update process becomes more complex
Solution Approach 1:
The system introduces an intermediary update mechanism that uses temporary buffer structures and transaction logs to manage atomic updates. The intermediary layer handles the complexity of maintaining consistency by coordinating updates across different decision tree sections, ensuring that either all changes are applied successfully or none are, thus maintaining update consistency while managing complexity through structured intermediation.
Data Source
AI summary
A system, apparatus, and method are provided for receiving one or more incremental updates including adding, deleting, or modifying rules of a Rule Compiled Data Structure (RCDS) used for packet classification. Embodiments disclosed herein may employ at least one heuristic for maintaining quality of the RCDS. At a given one of the one or more incremental updates received, a section of the RCDS may be identified and recompilation of the identified section may be triggered, altering the RCDS shape or depth in a manner detected by the at least one heuristic employed. The at least one heuristic employed enables performance and functionality of an active search process using the RCDS to be improved by advantageously determining when and where to recompile one or more sections of the RCDS being searched.