Client Device Latency in Automated Assistant Rendering
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Solution Overview
Problem
Existing automated assistant systems experience latency in rendering content responsive to user inputs due to delays in content generation and transmission between cloud-based components and client devices, leading to excessive network resource usage and increased client device resource consumption.
Innovation Solution
Implementing methods that allow for the simultaneous transmission and buffering of content related to multiple actions within a single multiple action request, enabling the client device to render outputs for subsequent actions before completing the rendering of previous actions, thereby reducing latency and network resource usage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If the client device waits for content to be generated and transmitted from cloud-based components before rendering each action output sequentially, then the system ensures proper content availability and rendering order, but the latency between rendering outputs for multiple actions increases and network resource usage becomes excessive
Solution Approach 1:
The system transmits content for multiple actions to the client device in advance, before the user completes interacting with the first output. The client device receives and buffers content for subsequent actions (second action, third action, etc.) while still processing and displaying the first action output. This preliminary transmission and buffering eliminates waiting time and reduces latency between rendering outputs.
Solution Approach 2:
The patent introduces a buffering mechanism as an intermediary between content transmission and rendering. The buffer temporarily stores content for multiple actions, allowing the client device to manage content availability independently of the cloud-based components' generation speed. This intermediary buffer decouples the rendering timeline from the content generation timeline, reducing latency while ensuring content is ready when needed.
2Loss of energy
If the client device transmits separate requests for each action to cloud-based components, then the system ensures proper handling of individual actions, but network resource usage becomes excessive
Solution Approach 1:
The system merges multiple separate action requests into a single batch request. Instead of transmitting individual requests for each action to cloud-based components, the client device sends one consolidated request that includes all actions. The cloud-based components process this single request and return content for multiple actions together. This merging dramatically reduces network resource usage by eliminating repeated connection overhead and data transmission for each separate request.
3Adaptability or versatility
If the cloud-based automated assistant components handle a large quantity of requests from a large quantity of disparate automated assistant clients, then the system provides robust automated assistant services to many users, but network resource consumption increases excessively
Solution Approach 1:
The patent enables multiple clients to benefit from consolidated request handling. By merging requests for multiple actions into single batch requests, the system reduces the total number of network transactions required to serve each client. This approach scales efficiently as more clients are added, since each client benefits from the same request consolidation optimization, reducing overall network resource consumption across the entire system.
Data Source
AI summary
Implementations relate to mitigating client device latency in rendering of remotely generated automated assistant content. Some of those implementations mitigate client device latency between rendering of multiple instances of output that are each based on content that is responsive to a corresponding automated assistant action of a multiple action request. For example, those implementations can reduce latency between rendering of first output that is based on first content responsive to a first automated assistant action of a multiple action request, and second output that is based on second content responsive to a second automated assistant action of the multiple action request.