Adaptive Policy Search Trees for Low-Latency Network Appliances
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current network processors utilize even boundary policy search trees, which result in unnecessary search levels and inefficiencies when applying network policies to high-volume, high-rate network traffic, leading to differential latency and reduced processing efficiency.
Innovation Solution
Implementing a non-equal boundary policy set search tree that adjusts search ranges based on the density of policies, allowing for smaller ranges where policies are dense and larger ranges where they are sparse, reducing the number of search levels required.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If an even boundary policy search tree is used, then the policy search structure is simple and uniform, but the number of search levels increases and processing efficiency decreases
Solution Approach 1:
The patent applies local quality by making the search tree boundaries adaptive rather than uniform. Different regions of the search tree have different boundary characteristics based on policy density. In regions with high policy density, the search tree uses finer granularity boundaries, while in sparse regions, it uses coarser boundaries. This localized adaptation optimizes the search path length for each specific region, resolving the contradiction between structural simplicity and processing efficiency.
Solution Approach 2:
The patent introduces dynamics by making the search tree structure adaptable to the actual distribution of policies. Rather than using fixed even boundaries, the search tree dynamically adjusts its boundary characteristics based on where policies are concentrated. This dynamic structure allows the system to optimize search performance according to the actual policy density in different regions, improving processing efficiency without significantly increasing structural complexity.
2Device complexity
If an even boundary policy search tree is used, then the search tree structure is uniform, but latency increases due to unnecessary search levels
Solution Approach 1:
The patent reduces latency by applying local quality to the search tree boundaries. Instead of using uniform even boundaries that create unnecessary search levels in all regions, the system uses fine-grained boundaries only where policies are densely packed. In sparse regions, coarser boundaries reduce the search depth. This localized optimization directly reduces the number of search levels traversed, thereby reducing policy application latency while maintaining manageable structural complexity.
3Productivity
If a non-equal boundary policy set search tree is implemented, then processing efficiency improves, but the search tree structure becomes more complex
Solution Approach 1:
The patent manages the complexity increase by systematically changing the boundary parameters based on policy density metrics. Rather than creating an arbitrary complex structure, the system derives the non-equal boundaries from measurable parameters such as policy concentration in different regions. This parameter-driven approach to structuring the search tree makes the complexity manageable and systematic, while still achieving the productivity gains from optimized search paths.
4Productivity
If a non-equal boundary policy set search tree is implemented, then search levels are minimized, but the structure becomes asymmetric
Solution Approach 1:
The patent embraces asymmetry as a deliberate design choice to improve policy search efficiency. The non-equal boundary structure creates an asymmetric search tree that reflects the actual asymmetric distribution of policies in the network. This asymmetric structure minimizes the search levels by directing the search more efficiently toward regions with higher policy density, accepting the increased structural complexity as a necessary trade-off for achieving superior search performance.
Data Source
AI summary
Various embodiments provide systems and methods for applying network policies to network traffic based upon a non-equal boundary search tree.