Adaptive Application Self-Update System Context Orchestration
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Solution Overview
Problem
Information handling systems face challenges in efficiently and adaptively updating applications due to varying user contexts and requirements, leading to suboptimal update timing and resource utilization.
Innovation Solution
An adaptive self-updating system within the information handling system, utilizing an identity context engine, system context engine, orchestrator, update controller, and external update resources to determine and execute updates based on specific contexts, such as user identity, system resource availability, and locale, ensuring timely and appropriate updates.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If updates are performed frequently to ensure application currency, then reliability is improved, but resource consumption and user disruption increase
Solution Approach 1:
The update system dynamically adjusts update frequency and timing based on real-time system state (resource availability, user activity patterns, criticality of updates). The orchestrator continuously monitors system context and adapts update schedules, transforming a static update mechanism into a dynamic one that optimizes between reliability and resource consumption based on current conditions.
Solution Approach 2:
The system changes key parameters (update timing, update frequency, resource allocation) based on system context. The identity context engine and system context engine analyze multiple parameters (user identity, system resources, locale, criticality) and adjust update parameters accordingly, allowing the system to maintain reliability while adapting resource consumption to actual needs.
2Reliability
If updates are performed immediately when available, then reliability is improved, but system performance and user experience deteriorate
Solution Approach 1:
The system performs preliminary actions by downloading and staging updates in advance during periods of low system utilization, before actually applying them. The orchestrator schedules update downloads and preparations during off-peak times, so that when updates are installed, the system is already prepared and can minimize performance impact on users.
Solution Approach 2:
The system continuously monitors system performance metrics and user activity as feedback, using this information to adjust update timing decisions. The system context engine receives feedback about current system state and feeds it back to the orchestrator, which then decides whether to proceed with updates or delay them until conditions are more favorable.
3Reliability
If a comprehensive update checking mechanism is implemented to ensure all updates are captured, then reliability is improved, but device complexity increases
Solution Approach 1:
The update checking mechanism is segmented into specialized components with specific responsibilities: the identity context engine handles user-specific update requirements, the system context engine handles system-state analysis, and the orchestrator coordinates between them. This segmentation allows each component to be relatively simple while the collective system achieves comprehensive update detection.
Data Source
AI summary
An information handling system, includes a processor to execute an application and an update system to determine to provide an update to the application. The update system includes an identity context engine to determine an identity context for the information handling system and a system context engine to determine a system context for the information handling system. The update system determines whether to retrieve an update manifest for the update based upon the identity context, the system context, and a manifest policy, determines whether to download the update based upon the identity context, the system context, and a download policy, and determines whether to install update based upon the identity context, the system context, and an installation policy.