Server-Side Time Stream Aggregation for Forecast Simulation
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Solution Overview
Problem
The existing forecasting systems face inefficiencies due to the resource-intensive process of transmitting multiple historic time streams from a server-side computing device to a client-side proxy, which prolongs processing time and consumes excessive computing resources.
Innovation Solution
Implementing a method to aggregate historic time streams before transmission, allowing the server-side computing device to process and transmit them efficiently, thereby reducing the number of calls and resource demand, and utilizing a forecast model to predict future time streams for new items.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If multiple historic time streams are transmitted individually from server to client, then data completeness is improved, but data transmission time increases
Solution Approach 1:
The patent combines multiple individual time stream data sets into a single aggregated data set before transmission. The server retrieves multiple time streams corresponding to different reference products and merges them into one consolidated data structure that includes all necessary historical data, thereby reducing the number of transmission operations while maintaining complete data availability for the forecasting model.
Solution Approach 2:
The server performs data aggregation and preprocessing operations before the client requests the data. By pre-computing and consolidating the time streams into a single aggregated data set on the server side, the system eliminates the need for multiple sequential retrieval operations at the client, thereby reducing overall data transmission time and network overhead.
2Measurement precision
If multiple calls are made to retrieve historic time streams, then data accuracy is improved, but computing resource consumption increases
Solution Approach 1:
The server automatically retrieves, aggregates, and prepares the complete set of historical time streams in response to a single client request. The server-side computing device autonomously performs the data collection and consolidation operations, eliminating the need for the client to make multiple separate calls, thereby reducing overall system resource consumption while maintaining data accuracy.
Solution Approach 2:
The system merges multiple data retrieval operations into a single server-side process. By consolidating the retrieval and aggregation of all required time streams on the server, the system reduces the total number of network calls and associated processing overhead, thereby lowering computing resource consumption while ensuring complete and accurate data is provided to the forecasting model.
3Productivity
If data processing is performed at client-side, then data transmission efficiency is improved, but client device processing capability is exceeded
Solution Approach 1:
Instead of having the client retrieve and process multiple separate time streams, the patent inverts the processing location by performing data aggregation on the server side. The server consolidates all required historical data into a single aggregated data set before transmission, thereby reducing the client's processing burden to merely receiving and using the pre-processed data for forecasting.
Solution Approach 2:
The server acts as an intermediary that performs data aggregation and preprocessing operations between the data repository and the client device. By introducing this server-side processing layer, the system offloads complex data consolidation tasks from the client device, thereby improving transmission efficiency while respecting the client's limited processing capabilities.
Data Source
AI summary
Methods, systems, and computer-readable storage media for data transfer with a forecast model, the method being executed by one or more processors and including: receiving, by a server-side computing device and from a client-side proxy, a query including a plurality of item references associated to a new item, retrieving, by the server-side computing device, a plurality of data sets from a repository, each of the plurality of data sets including a respective time stream corresponding to a respective item reference, providing, by the server-side computing device, a result data set by aggregating the plurality of data sets, and transmitting, by the server-side computing device, the result data set to the client-side proxy, for forecasting a future time stream of the new item using the forecast model.