Predictive UI Buffer for Network Latency Reduction
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Solution Overview
Problem
Server-based computer systems experience higher network latency due to the time taken to transmit and receive data across networks, affecting response time, which is exacerbated by the need to access and process large amounts of data, leading to potential system overload.
Innovation Solution
Implementing a system that anticipatorily loads minimal network-accessed information into a local storage space, allowing for immediate retrieval and execution of system actions when corresponding user inputs are selected, thereby eliminating network latency and preventing system overload.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If data is accessed from network repository in server-based systems, then system functionality is provided, but network latency increases response time
Solution Approach 1:
The system performs preliminary actions by predicting probable succeeding user inputs before they occur, pre-fetching and storing corresponding system actions and metadata in a local UI buffer. This eliminates network latency when the actual input is received, as the data is already locally available for immediate execution.
Solution Approach 2:
A local UI buffer is introduced as an intermediary between the network repository and the system execution layer. This buffer stores pre-fetched system actions and metadata locally, serving as a mediator that eliminates the need for real-time network access during user input processing, thereby reducing response time while maintaining system functionality.
2Adaptability or versatility
If large amounts of data are accessed and processed, then comprehensive system actions are available, but system overload occurs
Solution Approach 1:
Instead of loading all possible system actions into the UI buffer, the system applies partial action by only pre-fetching and storing the specific system actions corresponding to predicted probable succeeding user inputs. This selective approach provides necessary system functionality while avoiding the overhead of processing and storing excessive data, thus preventing system overload.
3Ease of operation
If network data transmission is performed, then system actions can be executed, but network latency affects response time
Solution Approach 1:
The system performs preliminary data retrieval by predicting user inputs and fetching corresponding system actions from the network repository before the actual inputs occur. This pre-fetching stores the data in a local UI buffer, eliminating network transmission delays during actual system execution and enabling immediate response to user inputs.
Solution Approach 2:
The system creates local copies of system actions and metadata in the UI buffer by pre-fetching them from the network repository. These local copies enable system execution without requiring real-time network data transmission, thereby eliminating network latency while maintaining the capability to execute system actions.
Data Source
AI summary
In an embodiment, the user input and a corresponding user input pattern is received on a computer generated user interface (UI). Based upon the user input pattern, a probable succeeding user input is predicted, and a network repository is queried to determine a system action corresponding to the probable succeeding user input. The system action may be an action that is estimated to be processed based upon the user input. This system action is processed to determine associated metadata, which is persisted in a UI buffer associated with the UI. A correlation between the succeeding user input and the predicted probable succeeding user input is determined; and based upon the correlation the metadata is retrieved from the UI buffer for execution.