Context-Based Computing Framework for Location Adaptation
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Solution Overview
Problem
Existing computing devices are unable to adapt to their operating environment's context, requiring significant manual intervention for reconfiguration when moved to different settings, leading to increased development costs and time to market.
Innovation Solution
A context-based computing framework that allows devices to automatically adapt by receiving context information from a context service, which identifies available resources and interaction characteristics based on the device's location, enabling seamless operation across varying environments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If computing devices use predefined tasks and fixed configurations, then device complexity is reduced and ease of manufacture is improved, but adaptability to different environments deteriorates and manual reconfiguration effort increases
Solution Approach 1:
The patent introduces a context service as an intermediary between the computing device and the environment. The context service receives context information from sensors and other sources, processes it, and provides relevant context data to the computing device. This mediator handles the complexity of environmental adaptation, allowing the device itself to remain relatively simple while gaining enhanced adaptability through the contextual information provided by the service.
Solution Approach 2:
The system performs preliminary actions by pre-defining context profiles and templates that describe various environmental contexts and associated device configurations. When a device enters a new environment, the context service matches the current context against these pre-defined profiles and automatically applies the appropriate configuration, eliminating the need for real-time complex decision-making and manual reconfiguration.
2Adaptability or versatility
If computing devices manually adapt to new environments, then adaptability is improved, but time consumption and development costs increase
Solution Approach 1:
The computing device is equipped with a context client that enables it to autonomously query the context service for relevant environmental information and automatically configure itself based on the received context data. This self-service capability allows the device to adapt to new environments without human intervention, significantly reducing reconfiguration time and eliminating the need for manual adaptation efforts.
Solution Approach 2:
The system implements a feedback mechanism where the computing device continuously monitors environmental changes through sensors and context information, queries the context service for updated context profiles, and automatically adjusts its configuration in response. This closed-loop feedback system enables rapid adaptation to changing environments, reducing both the time and complexity associated with manual reconfiguration.
Data Source
AI summary
An example context-based computing framework includes methods to configure a computer device. Some example methods include generating a request for access to computing resources available at a first location in response to determining the computer device has moved from a second location to the first location. Some example methods also include, based on context data contained in a response to the request, configuring an interface of an application of the computer device is configured to allow interaction with a subset of a set of features of a first computing resource of the computing resources. The context data is identified in the context profile and the context profile is associated with the first location. Some example methods further include interacting, via the interface of the application, with a first feature of the subset of the set of features of the first computing resource.