Dynamic Performance Indicator Adjustment for Edge Network UEs
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Solution Overview
Problem
Wireless communications systems face challenges in managing application client performance indicators, leading to adverse effects on user equipment (UE) performance, such as battery drain, processor overload, and reduced quality of service.
Innovation Solution
The system enables wireless communications between a UE and an edge server, allowing for the adjustment of default performance indicators to enhance UE performance. This is achieved through detection mechanisms that monitor empirical data and generate a modified performance profile, enabling the UE or edge data network to signal adjustments to performance constraints.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If application clients operate with default performance indicators, then service functionality is maintained, but UE performance deteriorates due to battery drain, processor overload, and reduced quality of service
Solution Approach 1:
The system dynamically adjusts performance indicators based on empirical data and network conditions. The UE monitors actual performance metrics and signals adjustments to the edge data network, enabling flexible adaptation of application client performance parameters to optimize energy consumption while maintaining service functionality.
Solution Approach 2:
The patent changes performance indicator parameters from static default values to dynamically adjusted values based on monitored empirical data. The system modifies performance constraints such as data rates, buffer sizes, and processing priorities to reduce energy consumption while preserving essential service functionality.
2Reliability
If application clients operate with default performance indicators, then service functionality is maintained, but UE performance deteriorates due to processor overload
Solution Approach 1:
The system implements dynamic adjustment of performance indicators based on real-time monitoring of processor utilization and empirical data. When processor overload is detected, the UE signals the edge data network to reduce performance constraints, thereby distributing processing load and preventing processor overload while maintaining service functionality.
Solution Approach 2:
The UE continuously monitors empirical data including processor performance metrics and provides feedback to the edge data network. This feedback loop enables the system to adjust performance indicators in response to processor overload conditions, ensuring service functionality is maintained without excessive processor utilization.
3Productivity
If legacy application clients are enabled to use edge services, then network efficiency is improved, but system complexity increases due to performance indicator management
Solution Approach 1:
The UE autonomously monitors empirical data and determines performance indicator adjustments without requiring complex external management. The device self-manages performance optimization by comparing actual performance against expected performance and automatically signaling adjustments to the edge data network, thereby improving network efficiency while minimizing the complexity burden on the system.
Data Source
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AI summary
Methods, systems, and devices for wireless communications are described. The method includes transmitting, to an edge data network via a wireless network, an indication of an adjustment to one or more performance indicators for an application client operating on the UE to receive service from the edge data network based on a UE modified performance profile for the application client and communicating application data traffic with the edge data network via the wireless network in accordance with adjusted performance indicators. The method includes receiving, from a UE via a wireless network, an indication of an adjustment to one or more performance indicators for an application client operating on the EE to receive service from the edge data network based on a UE modified performance profile for the application client and communicating application data traffic with the UE via the wireless network in accordance with adjusted performance indicators.