API Redirection for Limited OS via Intercept Layer
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Solution Overview
Problem
Conventional operating systems face issues when executing applications with unimplemented API calls, leading to run-time errors due to limited capability, power constraints, location, or other factors, which can result in inefficient operation or failure.
Innovation Solution
The implementation of an API intercept layer and a rules engine that dynamically redirects API calls to handle unimplemented API calls by intercepting and redirecting them to alternative entities such as GPUs, cloud services, or virtualized operating system images based on predefined rules.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If the entire operating system API is implemented locally on the computing device, then application compatibility and consistency are improved, but device complexity and resource requirements increase
Solution Approach 1:
The operating system API is segmented into multiple components: a core API layer implemented locally in the operating system image, and additional API components that can be dynamically loaded from external sources such as cloud services or remote devices. This segmentation allows the system to provide full API functionality without requiring all components to be present locally at all times.
Solution Approach 2:
An API compatibility layer or intermediary component is introduced that sits between the application and the operating system. This intermediary handles API calls, determining whether to route them to locally implemented functions or to external services, thereby maintaining application compatibility while reducing local implementation requirements.
2Reliability
If the entire operating system API is implemented locally on the computing device, then run-time errors are avoided, but power consumption and resource usage increase
Solution Approach 1:
The system dynamically determines which API components to load and execute based on current operational conditions, available resources, and application requirements. Rather than statically implementing all API functions locally, the system adapts its configuration to load only necessary components, reducing power consumption while maintaining reliability for critical functions.
Solution Approach 2:
The system changes operational parameters such as API implementation location (local vs. remote), caching strategies, and preloading behavior based on power availability, performance requirements, and application context. This allows optimization of power consumption while maintaining run-time reliability through adaptive parameter adjustment.
3Productivity
If API calls are redirected to external entities, then resource usage is optimized, but system complexity and latency increase
Solution Approach 1:
The system performs preliminary actions by pre-loading, caching, or pre-compiling frequently used API components and determining optimal execution locations in advance. This reduces the complexity of real-time redirection decisions and minimizes latency by having API implementations readily available when needed.
Solution Approach 2:
The system implements feedback mechanisms that monitor API call performance, latency, and success rates, using this information to dynamically adjust redirection strategies. This feedback loop helps optimize the balance between local execution and external redirection, managing system complexity while improving resource efficiency over time.
Data Source
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AI summary
Systems, methods and computer program products for facilitating the execution of application programs on computing devices with limited-capability operating systems by dynamically redirecting certain API calls are disclosed. Such systems, methods and computer program products provide one or more API intercept layers and a rules engine that facilitates the ability to make dynamic decisions on how to handle specific API calls. The redirection may be initiated for any number of reasons/factors/characteristics related to the computing device that render the operating system to be considered "limited capability," such as, for example, lack of local API implementation, power level, location, central processor unit usage, and any other pattern which determines that redirecting an API call to another entity is more efficient. Such entity may be a hardware component, a partitioned or virtualized operating system image, a network-based image or a cloud-based service.