Adaptive API Rate Limiting via Dynamic Token Generation
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Solution Overview
Problem
Existing rate limiting methods in servers are inadequate for managing legitimate spikes in load during peak hours and fail to differentiate between priority-based requests, leading to potential security vulnerabilities and inefficiencies.
Innovation Solution
Implementing adaptive rate limiting through a management server that generates a lightweight JSON token (JWT) based on the client's workload, allowing subsequent servers to dynamically adjust API call permissions according to the client's priority and workload, thereby enabling secure and efficient resource allocation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If static rate limiting is implemented with pre-set thresholds, then server security is improved, but legitimate spikes in load during peak hours are blocked and priority-based differentiation is lost
Solution Approach 1:
The patent implements dynamic rate limiting by replacing static pre-set thresholds with adaptive thresholds that are computed in real-time based on server workload conditions. The system dynamically adjusts the number of allowed API calls per client based on current server capacity, enabling the rate limiting mechanism to adapt to varying load conditions while maintaining security.
Solution Approach 2:
The patent changes the parameter of rate limiting from fixed static values to dynamic computed values. The system computes adaptive rate limits based on server workload metrics, transforming the rate limiting parameter from a constant to a variable that responds to changing system conditions, thereby resolving the contradiction between security and adaptability.
2Productivity
If priority-based differentiation is implemented, then efficient resource allocation is improved, but system complexity increases
Solution Approach 1:
The patent introduces a token as an intermediary mechanism that carries priority information from the client to the server. The token encapsulates workload-related data and priority levels, allowing the server to differentiate and prioritize requests without requiring complex integrated analysis of each request's context, thus managing complexity while enabling priority-based resource allocation.
Solution Approach 2:
The patent implements preliminary action by having clients compute their workload before making API calls and encode this information in advance within a token. This pre-computation and pre-packaging of priority information simplifies the server-side processing, as the server only needs to read and act upon the pre-computed token data rather than performing complex real-time analysis.
3Reliability
If token-based adaptive rate limiting is implemented, then differentiation between malicious and legitimate requests is improved, but additional processing overhead is introduced
Solution Approach 1:
The patent applies partial action by implementing token-based validation only when necessary for rate limiting decisions, rather than processing all requests through the full token validation pipeline. The system selectively uses token information based on the specific rate limiting context, reducing unnecessary processing overhead while maintaining accurate differentiation between malicious and legitimate requests.
Data Source
AI summary
According to examples, an apparatus may include a processor and a memory on which are stored machine-readable instructions that when executed by the processor, may cause the processor to receive a request from a client for a status of the client, and based on the status of the client, generate a token associated with application programming interface (API) calls to be received from the client. In some examples, the token may include a value representing a priority for determining an adaptive rate limiting of the API calls to be received from the client. The processor may send a response to the request, in which the response may include the status of the client and the token.


