Adaptive Multi-Window Resource Allocation for Smartphone Performance
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
The increased demand for multi-window scenarios on smartphones strains hardware resources, leading to poor user experiences due to screen lag and reduced frame rates when resources are insufficient.
Innovation Solution
An adaptive multi-window technology that detects multi-window scenarios, determines window priorities, monitors performance indexes, and reallocates resources by adjusting the profiles of windows using a resource re-allocation algorithm to optimize user experience.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If multi-window scenarios are supported with multiple windows running simultaneously, then user functionality and versatility are improved, but hardware resource consumption increases leading to screen lag and frame rate reduction
Solution Approach 1:
The system dynamically changes performance parameters (frame rate, resolution, CPU/GPU allocation) of individual windows based on their priority levels and current device resource availability. High-priority windows maintain high-performance parameters while low-priority windows automatically reduce to lower frame rates and resolutions, resolving the contradiction between supporting multiple windows and maintaining overall system reliability
Solution Approach 2:
The patent implements dynamic resource allocation where window priorities and performance parameters are not fixed but continuously adjusted based on real-time device state and user interactions. The system can promote or demote window priorities dynamically, and performance parameters adapt automatically as resources become available or constrained, enabling the system to maintain reliability across varying multi-window configurations
2Productivity
If hardware resources are allocated to multiple windows simultaneously, then multi-window performance is improved, but resource availability for individual windows decreases causing screen lag
Solution Approach 1:
Instead of applying uniform resource allocation across all windows, the system assigns different performance qualities to different windows based on their priority levels. High-priority windows receive superior local resource allocation (higher frame rates, resolutions, and processing power) while low-priority windows receive reduced allocation, enabling multi-window productivity without sacrificing the speed and responsiveness of critical applications
Solution Approach 2:
The patent segments the total hardware resources into distinct allocation pools for different priority levels. Rather than treating all windows equally, the system divides CPU time, GPU capacity, and memory bandwidth into segments that are distributed according to window priorities, allowing simultaneous multi-window operation while maintaining adequate frame rates in each segment
3Reliability
If resource re-allocation is performed dynamically based on performance indexes, then user experience is improved, but system complexity increases
Solution Approach 1:
The resource management system operates autonomously by continuously monitoring performance indexes (frame rate, CPU usage, memory availability) and automatically adjusting window priorities and resource allocation without requiring user intervention. The system serves itself by detecting performance degradation and reallocation resources accordingly, improving user experience while managing complexity through automation rather than manual control mechanisms
Data Source
AI summary
A method for adaptive multi-window technology includes detecting a multi-window scenario corresponding to a plurality of windows on an electronic device, determining priorities of the plurality of windows, monitoring a plurality of performance indexes of the electronic device, checking whether resource re-allocation is needed according to the performance indexes, determining targets of the plurality of windows if resource re-allocation is needed, and changing profiles of the targets according to a resource re-allocation algorithm.