Dynamic DDC Location Switching for XR Latency and Battery Use
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Solution Overview
Problem
Existing wireless communication systems face challenges in dynamically optimizing the distribution of computational tasks for extended reality (XR) devices, leading to sub-optimal power consumption, latency, and rendering quality due to inadequate consideration of network and device conditions.
Innovation Solution
The use of quality of service (QoS) metrics to dynamically determine the optimal location for distributed compute (DDC) by deriving potential DDC locations for XR application data, including UE, application server, or network node, based on QoS metrics, enabling selective indication to these entities.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Use of energy by moving object
If computational tasks are distributed to remote locations (application server or network node), then power consumption at the XR device is reduced, but latency increases due to communication overhead
Solution Approach 1:
The patent implements dynamic DDC location switching that adapts to changing network conditions (QoS metrics). The system transitions between static and dynamic compute locations (UE, application server, or network node) based on real-time channel quality, packet error rates, and latency measurements, optimizing the trade-off between power consumption and latency
Solution Approach 2:
The system changes operational parameters by switching the DDC location based on QoS metric thresholds. When channel quality degrades below a threshold, the system switches from remote processing (lower power) to local processing at the UE (higher power but lower latency), and vice versa when conditions improve
2Loss of time
If computational tasks are processed locally at the XR device, then latency is reduced, but power consumption increases
Solution Approach 1:
The system dynamically switches between local processing (XR device) and remote processing (application server/network node) based on real-time QoS metrics. When channel conditions are good, the system offloads computation to save power; when conditions deteriorate, it processes locally to maintain low latency
Solution Approach 2:
The system changes the operational state by switching DDC locations in response to QoS parameter changes. The decision to process locally or remotely is based on comparing measured QoS metrics against predefined thresholds, optimizing the latency-power trade-off
3Reliability
If DDC location is switched dynamically based on QoS metrics, then rendering quality and user experience are improved, but system complexity increases
Solution Approach 1:
The system implements feedback mechanisms by continuously monitoring QoS metrics (channel quality, packet error rates, latency) and using this information to make informed decisions about DDC location switching. This feedback loop ensures rendering quality is maintained while adapting to changing network conditions
Solution Approach 2:
The patent introduces a DDC manager as an intermediary component that handles the complexity of QoS metric evaluation and DDC location decision-making. This intermediary abstracts the complex switching logic from the XR device and UE, managing the complexity centrally while maintaining simple interfaces with other system components
4Use of energy by moving object
If remote processing is used to conserve battery life, then power consumption is reduced, but network dependency increases making the system vulnerable to quality issues
Solution Approach 1:
The system dynamically adjusts its operational mode based on network conditions. When remote processing is used to conserve battery, the system continuously monitors QoS metrics and switches to local processing when quality degradation is detected, ensuring reliability while optimizing power consumption
Solution Approach 2:
The system prepares for potential quality issues by having pre-configured fallback options. When remote processing is active, the system monitors QoS metrics and has the capability to switch to local processing as a cushion against network failures or quality degradation, protecting battery life while ensuring service continuity
Data Source
AI summary
Various aspects of the present disclosure generally relate to wireless communication. In some aspects, a computing device may obtain a quality of service (QOS) metric that is based at least in part on a user equipment (UE) linked to an extended reality (XR) device. The computing device may derive, using at least the QoS metric, a potential dynamic distributed compute (DDC) location for application data associated with the XR device, the potential DDC location comprising at least one of: the UE, an application server associated with the application data, or a DDC orchestrator at a network node. The computing device may indicate, selectively, the potential DDC location to at least one of: the UE, the application server, or the network node. Numerous other aspects are described.