External AI Inference Routing With Security Validation and Caching
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing cloud computing networks face challenges in managing inference requests directed to AI models external to the network, particularly in terms of security, resource allocation, and efficient processing across distributed servers.
Innovation Solution
A distributed cloud computing network manages inference requests by determining compliance with security rules, routing requests to appropriate servers, caching responses, and dynamically selecting AI models and resources based on request complexity and network conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If inference requests are directed to external AI models hosted outside the distributed cloud computing network, then access to diverse AI models is improved, but security control and network reliability deteriorate
Solution Approach 1:
The patent introduces an inference request gateway as an intermediary component that mediates between internal compute servers and external AI models. The gateway receives inference requests, validates them against security policies, manages authentication, and forwards approved requests to external models. This intermediary layer enables access to external AI models while maintaining security control within the distributed cloud computing network.
2Adaptability or versatility
If inference requests are processed by routing to external destinations, then model availability is improved, but processing latency and network overhead increase
Solution Approach 1:
The patent implements preliminary actions by pre-validating inference requests against security policies before forwarding to external models, pre-establishing authentication credentials, and pre-configuring routing paths. The inference request gateway performs security validation and authentication in advance, so that when requests are forwarded to external AI models, the processing latency is minimized because the security checks are already complete.
3Reliability
If security validation is performed for each inference request to external models, then security reliability is improved, but processing complexity and computational overhead increase
Solution Approach 1:
The patent creates a universal inference request gateway that handles multiple functions: security validation, authentication, request routing, and response management. This single multi-functional component consolidates what would otherwise be separate complex processes, reducing overall processing complexity while maintaining comprehensive security validation for all inference requests to external models.
Data Source
AI summary
A compute server of a distributed cloud computing network receives an inference request that is directed to an AI model hosted at a destination external to the distributed cloud computing network. The compute server determines that the inference request satisfies security rules associated with the AI model. Upon determining that the inference request is not answerable from a cache, the compute server transmits the inference request to the AI model hosted at the external destination. The compute server receives an inference response from the AI model in response to the inference request, transmits the inference response, and stores the inference request and the inference response in cache.