Edge Compute Platform Shared Customizable Functions
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Solution Overview
Problem
Edge computing imposes a burden on customers to develop, deploy, and manage customer-defined functions, leading to inefficient use of distributed platform compute resources due to redundant or inefficiently coded functions being executed simultaneously across different network locations.
Innovation Solution
An edge compute platform provides shared access to a common set of customizable functions that can be executed from various network edge locations, allowing customers to use these functions without coding or managing them, and dynamically optimizes content by caching and reusing output with transformation parameters, reducing the need for repeated execution and resource consumption.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If customers define and execute their own functions at edge locations, then customization and control are improved, but device complexity and resource consumption increase due to redundant function instances
Solution Approach 1:
The patent merges multiple customer-specific function instances into a single shared function instance at the edge location. The shared instance serves multiple customers by dynamically adapting its behavior based on customer identifiers included in requests, thereby eliminating redundant code deployment and reducing compute resource consumption while maintaining full customization capability for each customer
Solution Approach 2:
The shared function instance is designed to be universal by accepting customer-specific parameters and configuration data in its input, allowing it to perform multiple customer-specific tasks through a single instance. This multi-functionality approach enables one function to serve many customers with different requirements without needing separate instances for each
2Adaptability or versatility
If the same function is executed repeatedly for different users at the same network location, then user-specific customization is improved, but productivity decreases due to redundant execution
Solution Approach 1:
The system performs preliminary actions by pre-processing requests to extract customer identifiers and configuration parameters before invoking the shared function. This preliminary preparation allows the shared function to quickly adapt its behavior without re-executing setup code for each user, thereby improving execution efficiency while maintaining user-specific customization
Solution Approach 2:
Instead of copying and deploying separate function instances for each customer, the system uses a single shared function instance that is dynamically configured through parameter passing. The function receives customer-specific data as input parameters, effectively creating a virtual copy of the customized function behavior without the overhead of actual instance replication
Data Source
AI summary
Provided is an edge compute platform (“ECP”) for serving optimized content from local cache or from output of a shared customizable function executed by a compute device at the network edge on behalf of different customer content such that the function is not redundantly deployed for different customer content, and is not be executed each time the same variant of the optimized content is requested. The ECP may canonicalize first transformation parameters of a received original request according to a transformation parameter definition of a particular function that is implicated by the original request, may generate second transformation parameters with a different ordering than the first transformation parameters as a result of the canonicalization, may generate a variant of the original file by inputting the second transformation parameters to the particular function, and may provide the variant in response to the original request.