Context Model Inference Service for Mobile Device Memory Optimization
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Solution Overview
Problem
Conventional context-aware technologies face challenges due to excessive memory utilization, computation costs, and energy drain from processing and storing all collected context data, limiting their effectiveness and user benefits.
Innovation Solution
Implementing a method where context data from electronic devices is used to identify and provide compatible context models, utilizing a crowd sourcing approach where context models are uploaded to a server for analysis and distribution to devices, optimizing context models for efficient use without overburdening the device with redundant data processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional context sensing mechanism processes and stores all collected context data, then complete context information is available, but memory utilization and computation costs increase excessively
Solution Approach 1:
The patent extracts only the essential context information from collected data by using context models that represent typical context patterns. Instead of storing all raw context data, the system extracts and stores only the modeled context information that is necessary for context-aware services, thereby reducing memory utilization while maintaining reliability.
Solution Approach 2:
The patent performs preliminary action by pre-defining context models that represent expected context patterns before actual context sensing occurs. These pre-established models allow the system to filter and process context data more efficiently, storing only information that matches the predefined models, thus reducing both memory usage and computation costs.
2Reliability
If conventional context sensing mechanism processes all collected context data, then accurate context awareness is achieved, but computation costs increase excessively
Solution Approach 1:
The system extracts only the relevant context features that match predefined context models, rather than processing all collected context data. This extraction approach maintains context awareness accuracy by focusing on essential patterns while significantly reducing computation costs by eliminating processing of redundant information.
Solution Approach 2:
The patent changes the parameter representation by transforming raw context data into standardized context model parameters. This transformation allows for more efficient processing and comparison, reducing computation costs while maintaining the accuracy needed for reliable context awareness through standardized parameter matching.
3Reliability
If device stores and processes all context data, then comprehensive context information is maintained, but energy consumption increases
Solution Approach 1:
The system extracts only the essential context information needed for maintaining reliability, storing it in compressed context model format. This extraction and compression approach ensures comprehensive context data availability is maintained through the models while significantly reducing energy consumption associated with storing and processing raw data.
4Productivity
If context models are provided to electronic device, then context-aware services are optimized, but device receives additional data provisioning overhead
Solution Approach 1:
The patent uses copying by providing pre-defined context models to the electronic device instead of requiring the device to generate them independently. These copied models from the server reduce the provisioning overhead by eliminating the need for devices to collect and process large amounts of data to create their own context models, thereby optimizing context-aware service efficiency.
Data Source
AI summary
The exemplary embodiments of the invention provide at least a method, apparatus and system to perform operations including receiving context data from an electronic device, causing, at least in part based on the received context data, an identification of at least one context model compatible with the electronic device, and causing, at least in part, provision of the electronic device with the at least one compatible context model. In addition, the exemplary embodiments of the invention further provide at least a method, apparatus and system to perform operations including causing, at least in part, a provision of context data associated with an electronic device to a context inference service, in response, receiving a context model from the context inference service, and causing adaptation of the received context model as a current context model of the electronic device.