Database Record Update Time-Out Reduction
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Solution Overview
Problem
Existing methods for updating records in databases over a communications network often result in time-outs due to overburdened channels, as the quantity of information to be downloaded is not optimally estimated, leading to inefficiencies in data transfer and database synchronization.
Innovation Solution
A system and method that select database records for download based on date-time stamp values within a specified range, allowing for the use of multiple threads to concurrently download records within this range, thereby reducing the load on communication channels and improving the efficiency of database updates.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the quantity of information to be downloaded is not optimally estimated, then the database update process can be simple, but time-outs occur due to overburdened communication channels
Solution Approach 1:
The system performs preliminary actions by estimating the quantity of information to be downloaded before initiating the download process. The application server determines a time range based on previous responses and predicts the information volume, allowing it to prepare appropriate download parameters and avoid overburdening communication channels before the actual data transfer occurs.
Solution Approach 2:
The system uses feedback from previous download responses to improve future information estimation. The application server analyzes previous responses containing date-time stamp delta values and record update quantities, then applies this feedback to generate forecasts for upcoming downloads, dynamically adjusting the time range and expected information volume based on historical performance data.
2Productivity
If a large volume of data records is downloaded concurrently, then the database synchronization speed is improved, but the communication channel becomes overburdened causing time-outs
Solution Approach 1:
The system applies partial action by downloading only the necessary portion of data records within a predicted time range rather than attempting to download all available records. The application server forecasts the information volume and adjusts the download scope accordingly, performing slightly less than a full download to prevent communication channel overload while still achieving timely synchronization.
Solution Approach 2:
The system dynamically adjusts the download parameters based on real-time conditions and historical data. The time range and information volume predictions are not fixed but are dynamically determined based on previous responses and current system state, allowing the download process to adapt to varying communication channel capacities and data change rates.
3Quantity of substance
If the time range for record selection is increased, then more records can be updated, but the information volume increases causing communication overload
Solution Approach 1:
The system changes parameters by optimizing the time range selection based on forecasted information volume. Rather than using a fixed or maximally extended time range, the system adjusts the time range parameters to achieve an optimal balance between the number of records updated and the communication load, preventing overload while ensuring sufficient records are synchronized.
Data Source
AI summary
A system and method to reduce the incidence of communications network time outs by tailoring the time length specified by an initial date time stamp and an ending date time stamp ranges of a new record update query request to be less likely to direct a responding system(s) to responsively communicate a count of individual record updates and/or a combined information volume that overburdens a communications channel, protocol or mode to cause a time-out. The number of record updates received in response to previous update queries are observed. In view of these observed query responses, the date time stamp ranges of the new update requests specified by the initial date time stamp and the ending date time of a new potential query are limited in magnitude to be unlikely to cause responding messages to contain a higher quantity of record updates than a preselected quantity of record updates and/or data volume.