Predictive Controller Reduces Cloud Application Latency
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Solution Overview
Problem
Remote or cloud-based applications experience noticeable latency in responding to user inputs due to inherent delays in networking round-trip times, leading to lag in interactive applications like simulations and virtual reality.
Innovation Solution
The Predictive Controller employs machine-learned predictive models, such as Hidden Markov Models, to anticipate user inputs based on prior interactions and psychological states, reducing latency by applying predicted inputs to applications before actual user responses are received, and providing feedback when predictions differ from actual inputs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If remote or cloud-based applications are used, then application hosting flexibility and scalability are improved, but latency in responding to user inputs increases due to networking round-trip times
Solution Approach 1:
The system applies predictive models to anticipate user inputs before they are actually made. The predictive controller analyzes patterns from prior user interactions and generates predicted inputs in advance, allowing the remote application to prepare responses beforehand. This preliminary action on the input side compensates for the networking delay, making the system respond as if the input was received earlier.
2Loss of time
If predictive models are applied to anticipate user inputs, then latency is reduced, but device complexity increases due to machine learning components
Solution Approach 1:
The predictive controller creates simplified copies or representations of user behavior patterns through trained predictive models. Instead of implementing complex real-time analysis of user psychology and intent, the system uses pre-trained models that capture essential input patterns. These model copies enable fast prediction without requiring the full complexity of actual user cognitive processes.
Data Source
AI summary
A “Predictive Controller” operates with any type of controller or user input device to predict user inputs or responses to a current state of an application. A predictive model of the current state of the application is applied to prior user inputs to jointly predict a current user-specific psychological state or profile of the user and a predicted next user response or input. The predicted response or input is provided as the user input to the particular application prior to receiving the actual user input, thereby reducing latency of the response of the application to that actual user input. In addition, a tangible feedback corresponding to the predicted next user input is provided. Further, the predictive capabilities of the Predictive Controller can be applied to locally or remotely hosted instances of the application to reduce latencies associated with user inputs received from any type of controller or user input device.