Dynamic Query Rate Limiting via Control Plane Segmentation
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Solution Overview
Problem
Current systems face challenges in managing query handling efficiently, particularly in mobile applications, where server overload and resource consumption can lead to performance issues and responsiveness problems due to varying query types, rates, and network conditions.
Innovation Solution
Implementing a control plane and proxy system that dynamically determines rate-limiting parameters based on query-related resource consumption, performance measurements, and statistical data to filter and manage queries, thereby optimizing query processing and reducing server overload.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the server handles all incoming queries without filtering, then complete query processing capability is maintained, but server overload and resource consumption increase
Solution Approach 1:
The system segments query handling into two distinct paths: a control plane that processes control plane queries (CP queries) and a data plane that handles data plane queries (DP queries). This segmentation allows the server to prioritize and manage different query types separately, preventing overload by controlling the flow of CP queries while maintaining efficient handling of DP queries through caching mechanisms.
Solution Approach 2:
A rate limiting mechanism acts as an intermediary between query incoming and server processing. This intermediary monitors and controls the rate of CP queries, filtering out excessive requests before they can overload the server. The rate limiter serves as a buffer that maintains system reliability while protecting against productivity degradation from overload.
2Productivity
If rate limiting is applied to filter queries, then server overload is reduced, but query processing delay increases
Solution Approach 1:
The rate limiting parameters are made dynamic rather than static. The system adjusts rate limiting thresholds and caching strategies based on real-time server load conditions, query patterns, and resource availability. When server capacity is high, more queries are processed immediately; when load increases, rate limiting becomes more aggressive. This dynamic adaptation minimizes processing delays while maintaining effective load management.
Solution Approach 2:
The system changes key parameters such as cache expiration times, rate limiting windows, and query prioritization weights based on observed performance metrics. By monitoring server response times, resource utilization, and query volumes, the system dynamically adjusts these parameters to optimize the balance between filtering effectiveness and processing speed, reducing unnecessary delays.
3Loss of time
If caching is used to store query results, then response time for repeated queries improves, but memory resource consumption increases
Solution Approach 1:
The caching system applies local quality by storing cached results selectively rather than universally. Different cache strategies are applied to different query types: CP queries may use shorter cache durations with lower memory allocation, while DP queries with expensive computations use longer cache times. The system also implements hierarchical caching with different memory allocation levels, ensuring that frequently accessed results occupy premium memory while less critical data uses smaller allocations.
Solution Approach 2:
The system implements partial caching by selecting only the most beneficial queries for caching based on criteria such as query frequency, computational cost, and result size. Rather than caching all queries, the system identifies and caches only those queries where the memory investment yields the greatest time savings. This partial action approach optimizes the memory-time tradeoff by focusing resources on high-value cache candidates.
Data Source
AI summary
Embodiments are disclosed of systems and/or techniques for rate-limiting query-type requests, such as including content-type requests, to computing and/or networking devices, such as, for example, servers, capable of communicating over a computing and/or communications network.