Cloud Access Server Pre-Loading for Authentication Latency
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Cloud-based access servers face challenges in reducing latency when processing a high volume of authentication requests, particularly due to the need to fetch and evaluate various data dependencies associated with each request.
Innovation Solution
The implementation of advanced authorization requests that anticipate future user interactions by pre-loading dependent data, combined with the use of triggering events to preprocess frequently invoked access policies, and the deployment of a replay service to generate and evaluate preemptive authorization requests based on processing snapshots.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If the access server processes authentication requests in real-time by fetching and evaluating data dependencies, then authentication accuracy is maintained, but processing latency increases
Solution Approach 1:
The system performs preliminary actions by pre-evaluating authentication requests before they are actually needed. When a user logs in, the system anticipates future authentication requests and pre-fetches, pre-evaluates, and caches the required data dependencies and policy decisions. This allows subsequent authentication requests to be served from cache with minimal latency while maintaining full evaluation accuracy when cache misses occur.
Solution Approach 2:
The system dynamically adapts its processing approach based on real-time conditions. It monitors authentication patterns, cache hit rates, and system load to dynamically adjust the degree of pre-processing and caching. When latency is high, the system increases pre-processing; when accuracy concerns arise, it reduces caching and performs full evaluations, creating a dynamic balance between the two competing requirements.
2Productivity
If the access server processes a high volume of authentication requests concurrently, then service capacity increases, but processing latency increases due to resource contention
Solution Approach 1:
The system performs authentication evaluations in advance during low-load periods and caches the results. When authentication requests arrive during high-volume periods, the system serves pre-evaluated results from cache rather than performing real-time evaluations, thereby decoupling processing throughput from latency and allowing high concurrency without proportional latency increases.
Solution Approach 2:
The system maintains continuous useful action by having worker threads constantly pre-evaluate authentication requests even during idle periods. This ensures that evaluation work is continuously performed in the background, building up a cache of results that can be rapidly served during peak demand, maximizing resource utilization while maintaining low latency.
3Loss of time
If the access server pre-loads all possible data dependencies for anticipated requests, then latency is reduced, but memory resource consumption increases
Solution Approach 1:
The system applies local quality by caching data dependencies selectively based on their specific characteristics and usage patterns. Instead of uniformly caching all possible data, it identifies and caches only the most frequently accessed dependencies and policies relevant to each user's authentication pattern. This localized, targeted caching approach minimizes memory consumption while maximizing latency reduction for the most critical cases.
Solution Approach 2:
The system performs partial pre-loading by fetching and caching only a subset of potentially needed data dependencies rather than all possible data. It uses heuristics and historical patterns to determine which data to pre-load, accepting that some anticipated requests may experience increased latency (excessive action in the opposite direction) rather than pre-loading everything, thus balancing memory usage against latency reduction.
Data Source
AI summary
Disclosed are apparatuses, systems, and techniques that improve efficiency and decrease latency of processing of authorization requests by cloud-based access servers that evaluate access rights to access various cloud-based services. The techniques include but are not limited to generating and processing advanced authorization requests that anticipate future authorization requests that may be generated by cloud-based services. The techniques further include processing of frequently accessed policies and policy data dependencies and preemptive generation and processing of authorization requests that are replicated from existing authorization requests.