Dynamic Connection Logic for Data Chunk Download Speed
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Downloading large data files is time-consuming, especially with poor internet connections, and existing methods often slow down when using multiple simultaneous connections, while data integrity checks are inefficient and can't start until the file is fully downloaded.
Innovation Solution
A system and method that dynamically adjust the number of simultaneous connections during data file downloads to optimize speed, using a logic engine to ramp up or down connections, and implement file hashing by parts to enable real-time integrity validation and resume capabilities.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If multiple simultaneous connections are used for downloading, then download speed may increase, but download time can actually increase under certain circumstances
Solution Approach 1:
The system dynamically adjusts the number of simultaneous connections during the download process. It starts with a limited number of connections and progressively increases them as the download progresses, rather than using a fixed number of connections throughout. This dynamic adjustment allows the system to optimize between connection overhead and throughput based on actual download conditions.
Solution Approach 2:
The system performs periodic evaluations of download progress and connection effectiveness. At regular intervals, it assesses whether the current number of connections is optimal and adjusts accordingly. This periodic review mechanism ensures that the system adapts to changing network conditions and download states, preventing the use of excessive connections that would increase overhead and actual download time.
2Reliability
If data integrity checks are performed after file download, then validation can be completed, but validation time is lost and cannot begin until download finishes
Solution Approach 1:
The system performs data integrity validation in parallel with the download process rather than sequentially. By calculating hash values for download chunks simultaneously as they are being transferred, the system eliminates the waiting time that would otherwise occur after download completion. This preliminary action ensures that validation begins immediately without delaying the download process.
Solution Approach 2:
The system divides the file into multiple chunks and validates each chunk independently during its download. This segmentation allows integrity checks to be performed on individual portions of the file simultaneously with their transfer, rather than waiting for the entire file to download before validation begins. The segmented approach enables parallel processing of download and validation operations.
3Productivity
If a fixed number of connections is used for download, then setup is simple, but download speed cannot be optimized under varying network conditions
Solution Approach 1:
The system continuously monitors download performance and network conditions, using this feedback to adjust the number of simultaneous connections. By measuring actual throughput, error rates, and time-to-complete for each chunk, the system determines whether increasing or decreasing the connection count would improve overall download speed. This feedback-driven adjustment optimizes productivity while keeping the control logic manageable.
Solution Approach 2:
The system automatically manages connection adjustments without requiring user intervention or complex manual configuration. The download client autonomously evaluates its own performance metrics and makes intelligent decisions about connection management. This self-service approach simplifies the user experience while implementing sophisticated optimization, reducing the apparent complexity despite the intelligent control mechanisms.
Data Source
AI summary
Systems and methods are provided that may be implemented to adjust or otherwise vary the number of simultaneous and separate connections that are employed for downloading separate data chunks of a single data file across a network from a single backend data source. A common file hashing algorithm may be extended to provide hashing by parts on multiple sets of data bytes, and may be implemented together with connection logic executing on a frontend client system and the leveraging of backend components.