Reduced Policy Evaluation for Web Server Latency
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Solution Overview
Problem
The evaluation of policies in web servers for determining what content to display to users is time-consuming, leading to latency issues, especially when dealing with large datasets and multiple concurrent users, which can result in a poor user experience due to delays.
Innovation Solution
The implementation of reduced policies that selectively remove rules to decrease evaluation costs while maintaining accuracy, using techniques such as rule evaluation suspension and optimization scripts to create faster policy evaluation processes, allowing for quicker content selection and display.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If full policy evaluation is performed to ensure security and accuracy, then policy enforcement reliability is improved, but system latency increases
Solution Approach 1:
The patent segments the policy evaluation process into multiple phases: a fast evaluation phase that checks only critical rules first, and a complete evaluation phase that executes all rules if needed. This segmentation allows the system to achieve fast response times for most requests while maintaining full policy enforcement reliability when required.
Solution Approach 2:
The patent implements partial policy evaluation by executing only a subset of rules (those most likely to affect the decision or those with highest priority) rather than all rules. This partial action approach reduces evaluation time while maintaining sufficient reliability for the majority of cases, with the option to perform complete evaluation when confidence is low.
2Measurement precision
If all policy rules are evaluated to ensure accurate content selection, then policy accuracy is improved, but processing speed deteriorates
Solution Approach 1:
The patent performs preliminary actions by pre-sorting and prioritizing policy rules based on their likelihood to affect the decision outcome. The evaluation process then proceeds through rules in priority order, allowing the system to achieve accurate results quickly in most cases by stopping early when a decisive rule is found, while maintaining the capability to evaluate all rules if needed for complex cases.
Solution Approach 2:
The system performs partial policy evaluation by executing only the necessary subset of rules required to make a confident decision. By analyzing rule priorities and interdependencies, the system determines when a partial evaluation is sufficient to achieve accurate content selection without the overhead of evaluating all rules, thereby improving processing speed while maintaining policy accuracy.
Data Source
AI summary
Technology for policies with reduced associated costs is disclosed. A policy may include an ordered rule set. When evaluated, the highest priority rule in the order that does not skip may control the policy outcome. Rules within a policy may have associated costs, such as data fetch and evaluation costs. In some contexts, it may be less important to evaluate every rule than to evaluate the policy quickly. Reduced policies that have one or more rules removed or that skip evaluation of some rules may be created for these contexts. When a rule of a policy is skipped, it may result in a possibility of a false allow or false deny. In some cases, rules may be duplicative. Removal or skipping of duplicative rules does not increase the possibility of a false allow or false deny. By using reduced policies in identified contexts, policy evaluation costs may be reduced.