Assistant Task Offloading Using Processing Rate Under Hardware Disparities
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing systems rely solely on signal strength metrics for determining whether to offload assistant-related processing tasks, leading to inefficiencies and processing delays due to disparities in network hardware, particularly in vehicles with different antenna capabilities compared to cellular phones.
Innovation Solution
Implementing network metrics such as processing rate and data reception rate from the server computing device to determine whether to offload tasks, allowing for local processing when connection status is poor, thereby reducing latency and resource usage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If signal strength metrics are used to determine whether to offload processing tasks, then the decision-making process is simple and fast, but the accuracy of the decision is poor due to hardware disparities between different devices
Solution Approach 1:
The patent changes the parameter used for connection status determination from signal strength to processing rate. Instead of relying on the antenna's signal strength metric, the system measures the actual processing rate of data packets between the client device and server, which provides a more accurate indication of effective connection status regardless of hardware differences.
2Reliability
If server processing is used for all tasks, then processing accuracy is high, but network resource usage increases and latency occurs when connection is poor
Solution Approach 1:
The patent implements dynamic task offloading decisions based on real-time processing rate measurements. The system continuously monitors the processing rate and adjusts whether to use server or local processing accordingly, making the processing architecture flexible and adaptive to current network conditions rather than static.
Solution Approach 2:
The system uses feedback from processing rate measurements to inform subsequent offloading decisions. By measuring the actual data processing rate and comparing it against thresholds, the system receives feedback about connection quality and adjusts its processing strategy accordingly, creating a closed-loop control system.
3Loss of energy
If local processing is used, then network resource usage is reduced, but processing capability is limited compared to server processing
Solution Approach 1:
The patent enables dynamic switching between local and server processing based on measured processing rates. When processing rates indicate good connection status, the system utilizes server processing for enhanced capability; when rates indicate poor connection, it switches to local processing to conserve network resources, optimizing the trade-off dynamically.
4Ease of operation
If threshold signal strength is used to determine connection suitability, then the decision rule is simple, but processing delays occur when hardware disparities exist
Solution Approach 1:
The patent changes the measurement parameter from signal strength to processing rate, which provides a more accurate reflection of actual connection performance. This parameter change maintains decision rule simplicity while eliminating the processing delays caused by hardware disparities, as processing rate directly measures effective data transmission capability.
Data Source
Figure 1A
Figure 1B
Figure 1C
AI summary
Implementations set forth herein relate to off-loading, or temporarily ceasing such off-loading, computational tasks to a separate computing device based on a network metric(s) that is not limited to signal strength. Rather, a network metric for determining whether to continue relying on a network connection with a server computing device for certain computational tasks can be based on a current, or recent, interaction with the server computing device. In this way, an application executing at a computing device having a powerful antenna - but an otherwise limited network velocity, can determine to temporarily rely exclusively on local processing. For instance, an automated assistant can temporarily cease communicating audio data to a remote server computing device, during a dialog session, in response to determining a network metric fails to satisfy a threshold - even though there may appear to be adequate signal strength to effectively transmit the audio data.