Dynamic Peripheral Grouping for IHS Power and Thermal Optimization
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
In shared workspaces, configuring groups of peripheral devices to optimize performance and user experience is challenging due to cross-effects on Information Handling System (IHS) metrics, requiring manual experimentation to reduce system load and improve battery, thermal, and connectivity metrics.
Innovation Solution
Systems and methods for selecting and configuring grouped peripherals in shared workspaces by grouping devices into classes based on performance metrics, such as processing load, memory, battery level, power consumption, and connectivity, and dynamically switching between integrated and external devices to optimize performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If multiple peripheral devices are connected in shared workspaces, then device functionality and user experience are improved, but system performance metrics (processing load, memory, battery level, power consumption, thermal characteristics, connectivity) deteriorate
Solution Approach 1:
The system dynamically selects and switches between peripheral devices based on real-time performance metrics. The IHS monitors processing load, memory usage, battery level, power consumption, thermal characteristics, and connectivity status, then automatically switches between integrated and external devices to optimize the balance between functionality and power consumption.
Solution Approach 2:
The system changes operational parameters by monitoring performance metrics and adjusting device selection accordingly. When performance metrics indicate optimal conditions, higher-functionality external devices are activated; when metrics deteriorate, the system switches to integrated devices with lower power consumption requirements.
2Adaptability or versatility
If multiple peripheral devices are connected in shared workspaces, then device functionality and user experience are improved, but system performance metrics (processing load, memory, battery level, power consumption, thermal characteristics, connectivity) deteriorate
Solution Approach 1:
The system performs automatic device selection and switching without requiring manual user intervention. The IHS autonomously monitors performance metrics, evaluates available peripheral devices, and switches between integrated and external devices based on current system state, eliminating the need for manual experimentation and configuration.
Solution Approach 2:
The system implements a feedback loop where performance metrics are continuously monitored and used to inform device selection decisions. The IHS receives feedback from sensors monitoring processing load, memory usage, battery level, power consumption, thermal characteristics, and connectivity, then adjusts device configuration accordingly to maintain optimal performance.
3Reliability
If manual experimentation is performed to optimize device configuration, then performance optimization may be achieved, but time consumption and operational complexity increase
Solution Approach 1:
The system performs preliminary actions by pre-configuring and pre-evaluating available peripheral devices before they are needed. The IHS maintains an inventory of available devices with their characteristics and capabilities, so when device selection is required, the system can quickly match devices to current performance conditions without time-consuming manual experimentation.
Data Source
AI summary
Embodiments of systems and methods for selecting and configuring grouped peripherals in shared workspaces are described. In an illustrative, non-limiting embodiment, an IHS may include a processor and a memory coupled to the processor, the memory having program instructions stored thereon that, upon execution by the processor, cause the IHS to: group a plurality of devices available during a shared workspace session into a plurality of groups; transmit, to a remote service: (a) an indication of a performance metric, and (b) an indication of the plurality of groups; and receive, from the remote service, a selection of one device in each of the plurality of groups for use during the shared workspace session based, at least in part, upon the performance metric.


