Parallel AR Experience Control Under App Usage Budgets
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Solution Overview
Problem
Existing AR systems face inefficiencies in resource allocation and scaling, leading to suboptimal performance, increased costs, and system instability due to indiscriminate scaling of operations, which fails to account for individual resource demands and user behavior.
Innovation Solution
A system that dynamically scales operations of external AR applications while maintaining the quality of service for native AR applications, adjusting operations of external applications that exceed usage thresholds without affecting the native applications.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If AR operations are scaled indiscriminately to meet user demand, then system capacity and functionality are improved, but resource waste and operational inefficiency increase
Solution Approach 1:
The patent implements differentiated scaling strategies for different AR operations based on their individual characteristics and resource demands. Instead of uniform scaling, the system applies local quality by tailoring resource allocation to specific operational contexts, user behavior patterns, and resource requirements, thereby improving system capacity while avoiding resource waste.
Solution Approach 2:
The system dynamically adjusts the scaling of AR operations in real-time based on changing conditions including user behavior, resource availability, and operational priorities. This dynamic approach allows the system to adapt capacity flexibly without committing excessive resources, resolving the contradiction between system capacity and resource waste.
2Reliability
If AR operations are scaled uniformly to ensure system stability, then reliability is improved, but individual resource demands are not met optimally
Solution Approach 1:
The patent segments AR operations into distinct categories based on their resource requirements, priority levels, and user importance. This segmentation allows the system to apply different scaling strategies to different operation types, maintaining overall system stability while optimizing resource allocation for high-priority operations, thereby improving both reliability and productivity.
Solution Approach 2:
The system changes key parameters such as scaling factors, resource allocation weights, and priority thresholds based on real-time conditions. By dynamically adjusting these parameters, the system maintains stability through controlled scaling while improving productivity by allocating more resources to high-value operations when available.
3Productivity
If resource allocation is optimized for specific AR operations, then operational efficiency is improved, but system complexity increases
Solution Approach 1:
The patent implements self-service mechanisms where the AR operation scaling system automatically monitors its own performance, detects resource constraints, and adjusts scaling parameters without external intervention. This self-managing approach improves operational efficiency through optimized resource allocation while containing system complexity by eliminating the need for complex external control mechanisms.
Solution Approach 2:
The system incorporates feedback loops that continuously monitor resource usage, operational performance, and system state. This feedback mechanism enables automatic adjustment of resource allocation to maintain optimal efficiency while managing complexity through closed-loop control rather than complex open-loop configurations.
4Adaptability or versatility
If external AR applications are allowed to exceed usage budgets, then application functionality is improved, but native AR application performance deteriorates
Solution Approach 1:
The patent implements preliminary anti-action by establishing usage budgets and resource constraints for external AR applications before they can negatively impact native applications. The system proactively prevents external applications from exceeding allocated resources through preemptive throttling and resource reservation mechanisms, thereby protecting native application performance while still allowing external applications to function within reasonable limits.
Solution Approach 2:
The system allows external AR applications to perform partial operations within their usage budgets while throttling excessive actions that would compromise native application performance. This partial action approach enables external applications to maintain useful functionality without allowing them to consume excessive resources that would degrade the performance of native AR applications.
Data Source
AI summary
Systems, methods, and computer readable media for power and temperature attribution on mobile devices. Example methods include launching a native augmented reality (AR) application together with an external AR application on the user system. The example methods include determining that usage of the external AR application transgresses a usage budget for the external AR application and adjusting one or more operations of the external AR application without modifying operation of the native AR application in response to determining that the usage of the external AR application transgresses the usage budget for the external AR application.