Adaptive Payload File Generation for Collaborative Data Sharing
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Solution Overview
Problem
In collaborative product design and development environments, transferring large amounts of product data across geographically distributed locations is time-consuming, especially when network bandwidth is insufficient, leading to inefficiencies and delays due to underutilization of computing resources at both the source and target locations.
Innovation Solution
A method and data processing system that adaptively generates and sends payload files based on payload processing information, ensuring efficient use of resources by coordinating exporter and importer processes, dynamically adjusting payload file size, and deferring generation when necessary to maintain optimal processing capacity at both ends.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If huge amount of product data is transferred across geographically distributed locations, then complete product data sharing is achieved, but transfer time becomes excessive and network bandwidth is insufficient
Solution Approach 1:
The patent divides structured product data into multiple bounded-size subsets using recursive analysis and traversal. Each subset is then transferred independently in parallel across the network, reducing the time required to transfer the complete product data while maintaining data integrity and structure.
Solution Approach 2:
The patent performs preliminary analysis and division of product data into subsets before transfer begins. This pre-processing step enables parallel transfer operations and allows the system to optimize transfer parameters in advance, reducing overall transfer time.
2Ease of manufacture
If sequential operations are used for data export and import, then resource utilization is simple to manage, but computing resources at source and target locations remain unutilized during transfer
Solution Approach 1:
The patent implements parallel export and import operations where multiple subsets are being exported from the source location and imported at the target location simultaneously. This eliminates idle time for computing resources at both ends, as exporter processes and importer processes operate concurrently rather than sequentially.
Solution Approach 2:
The patent dynamically coordinates multiple exporter and importer processes that adapt their operation based on real-time conditions. The system manages parallel process execution and resource allocation dynamically, allowing computing resources to be fully utilized throughout the data transfer process rather than remaining static and underutilized.
3Loss of time
If parallel data transfers are initiated by dividing product data into subsets, then transfer time is reduced, but resource coordination complexity increases
Solution Approach 1:
The patent implements coordination mechanisms that monitor the state of parallel export and import operations and adjust resource allocation accordingly. This feedback-based coordination manages the complexity of parallel operations by dynamically responding to actual system conditions, ensuring efficient resource utilization without overwhelming complexity.
Data Source
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AI summary
The present invention provides a method and system for sharing product data in a collaborative environment (100, 500). In one embodiment, the method includes establishing a session for sharing product data between a source device (102) and a target device (104). The method includes adaptively generating one or more payload files (404A1-N-404N1-N) corresponding to the product data based on payload processing information (410). The payload processing information (410) includes number of payload files (404A1-N-404N1-N) waiting to be processed at the target device (104). Moreover, the method includes sending the one or more payload files (404A1-N-404N1-N) to the target device (104) over the product data sharing session such that the product data is reproduced at the target device (104) using the payload files (404A1-N-404N1-N).