Offline Upload Optimization via Batch Operation Merging
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Solution Overview
Problem
Existing systems face performance bottlenecks and scalability issues when multiple devices reconnect online simultaneously, leading to inefficient processing of modification operations in offline applications, as each operation is processed individually, resulting in increased workload and potential disruptions.
Innovation Solution
The solution involves logically combining modification operations at a backend system to reduce the workload, ensuring compatibility and optimizing uploads by merging operations such as create, update, and delete requests, rather than processing them individually, using a queue optimizer that analyzes and groups related operations into optimized units of work.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If individual modification operations are processed separately at the backend system, then each operation can be handled independently and simply, but system performance deteriorates and scalability is limited when multiple devices reconnect simultaneously
Solution Approach 1:
The patent merges multiple individual modification operations into a single batch operation. When multiple client devices reconnect to the backend system, their pending modification operations are grouped together and processed as one unified batch, rather than handling each operation separately. This combining approach maintains operational simplicity while dramatically improving system performance and reducing processing time.
2Reliability
If multiple modification operations are processed individually, then operation independence is maintained, but processing load increases and creates bottlenecks
Solution Approach 1:
The system combines multiple modification operations into a single batch processing unit. By grouping operations that can be processed together, the patent reduces the total number of processing events from N individual operations to 1 batch operation, thereby significantly reducing processing load and eliminating bottlenecks while maintaining the integrity and independence of each individual operation within the batch.
3Difficulty of detecting and measuring
If individual operations are uploaded and processed separately, then operation granularity is fine, but scalability is compromised as the number of client devices and operations increases
Solution Approach 1:
The patent transitions from processing operations in a one-dimensional sequential manner (one operation at a time) to a multi-dimensional batch processing approach. Multiple operations are grouped into batches that can be processed in parallel, effectively adding a temporal dimension to the processing architecture. This dimensional shift enables the system to scale efficiently as the number of client devices and operations increases, while still maintaining appropriate operation granularity through controlled batch sizes and grouping strategies.
Data Source
AI summary
Disclosed herein are system, method, and device embodiments for optimizing uploads for an offline scenario by merging requests. An embodiment operates by performing a plurality of modification operations over application storage, generating a first queue entry within a normal operations queue corresponding to a first modification operation of the plurality of modification operations, generating a second queue entry corresponding to a second modification operation of the plurality of modification operations, generating an optimized operations queue including an optimized queue entry combining the first queue entry and the second queue entry, and synchronizing the application storage with a remote storage system based on the optimized operations queue.