Predictive GUI Rendering for Cloud Service Broker Latency

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Solution Overview

Problem

Traditional graphical user interfaces (GUIs) experience delays due to back-end latency, leading to poor user experience, especially in high-load situations, and the integration of multiple cloud applications complicates GUI rendering, resulting in slow response times and extensive development requirements.

Innovation Solution

A system and method for dynamically creating user navigation interfaces based on prediction, using a predictor to validate and update GUI transition models, select likely transitions, and generate navigation trees, incorporating models like Ngram, hidden Markov, and maximum entropy Markov models, along with classifiers like SVM, decision trees, and random forests, to improve response times.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Loss of time

If traditional GUIs wait for back-end response before transitioning to next state, then data accuracy is ensured, but GUI response time increases and user experience deteriorates

Engineering Contradiction:
ImproveGUI response timeVSAvoiddata accuracy
Core Design Contradiction:
Loss of timeVSReliability

Solution Approach 1:

The system pre-loads and caches data from the back-end before the user actually requests it. The predictor analyzes user behavior patterns to anticipate which data will be needed next, retrieves it in advance, and stores it in a cache. When the user navigates to the predicted screen, the data is already available locally, eliminating the wait time while ensuring accuracy through pre-validated caching mechanisms.

Inventive Principle:
Principle #10Preliminary action

Solution Approach 2:

The system implements a feedback loop where the predictor continuously monitors actual user navigation patterns and compares them with predicted patterns. When predictions are validated or corrected against actual user behavior, the system learns and refines its prediction model. This feedback mechanism ensures that predictions become increasingly accurate over time, maintaining data reliability while optimizing response times.

Inventive Principle:
Principle #23Feedback

2Productivity

If GUI predicts user navigation to reduce wait time, then user experience improves, but prediction accuracy may be insufficient leading to incorrect pre-loads

Engineering Contradiction:
Improvenavigation efficiencyVSAvoidprediction accuracy
Core Design Contradiction:
ProductivityVSMeasurement precision

Solution Approach 1:

Instead of predicting only the single most likely next screen, the system predicts multiple possible next screens with varying probabilities and pre-loads data for several potential destinations. This excessive action ensures that even if the top prediction is incorrect, the user's actual destination is likely among the pre-loaded options, maintaining navigation efficiency while compensating for prediction limitations.

Inventive Principle:
Principle #16Partial or excessive action

Solution Approach 2:

The prediction model is dynamically adaptive, continuously adjusting its predictions based on real-time user behavior feedback. The system modifies prediction weights and probabilities as it learns from actual navigation patterns, making the prediction mechanism flexible and responsive to changing user preferences and contexts, thereby improving accuracy over time.

Inventive Principle:
Principle #15Dynamics

3Adaptability or versatility

If multiple cloud applications are integrated into single GUI, then functionality increases, but GUI rendering complexity and development requirements increase

Engineering Contradiction:
Improveapplication integrationVSAvoidGUI rendering complexity
Core Design Contradiction:
Adaptability or versatilityVSDevice complexity

Solution Approach 1:

The integrated GUI is segmented into modular components, each representing a separate cloud application or functional unit. Each module can be independently developed, rendered, and managed. The system composes these modular segments dynamically based on user predictions and current context, allowing high functionality through integration while maintaining manageable complexity through modular architecture.

Inventive Principle:
Principle #1Segmentation

Data Source

PatentEP3765992B1System and method for generating prediction based guis to improve GUI response times
Publication Date: 2023.11.22 CLOUDBLUE LLC
  • EP3765992B1 patent drawingFigure 1A~1B
  • EP3765992B1 patent drawingFigure 1C
  • EP3765992B1 patent drawingFigure 2

AI summary

A graphical user interface (GUI) (or a user navigation interface), is a common feature of computer systems and application well known to one having ordinary skill in the arts. In cloud service broker (CSB) environments, GUI rendering is more complicated because independent software vendors (ISV) distribute cloud applications (cloud services) through CSBs and allow different cloud applications to collaborate through standardized representational state transfer (RESTful) application program interfaces (API). If there are multiple applications that are integrated, the GUI may include numerous interfaces specifically tailored to the each of the specific applications. However, preparing all combinations of screens requires extensive development, which increases as more and more applications are integrated. The present disclosure relates to a system and method for dynamic creation of user navigation interfaces based on prediction, based on shared connector packages and predictive behavioral GUI model building, to enable faster GUI response times.