- Number
- 12360789
- Published
- 2025-07-15
- Filed
- 2021-09-07
- Assignee
- Disney Enterprises, Inc.
- Inventors
- MacDonald; John
- CPC
- G06F9/455; G06F30/20
- Verdict
- Set aside IT file-transfer modeling, plumbing
- Source
- Google Patents · FreePatentsOnline
Abstract
A system includes a computing platform having processing hardware, and a system memory storing a software code. The processing hardware is configured to execute the software code to identify a file transfer protocol among multiple file transfer protocols for transferring one or more file(s), to determine, using a test data sample and the file transfer protocol, one or more parameter(s) correlated with a time required for transferring the file(s) using the file transfer protocol, and to provide, based on the parameter(s), an algorithm for transferring the file(s) using the file transfer protocol. The processing hardware is further configured to perform, using the algorithm, a file transfer simulation of the file(s) using the file transfer protocol, to provide, using the file transfer simulation, data pooling parameters for transferring the file(s), and to estimate, based on the file transfer simulation and the data pooling parameters, an elapsed time for transferring the file(s).
Background
BACKGROUND (1) With the advent of big data and the ever growing use of cloud-based computing resources for performing data processing, the transfer of enormously large numbers of data files, such as millions of data files, for example, has become relatively commonplace. Accurately estimating the amount of time required to complete a large file transfer is important for efficient utilization of computing resources and network bandwidth. However, obtaining an accurate estimate for the time required to complete large file transfers between computing environments has proven to be challenging, due in part to the use of different file transfer protocols by different vendors. For example, although a naïve approach may assume that simply knowing the amount of data to be transferred and the capacity of bandwidth of the data transfer pipeline provided by a vendor enable a reasonable file transfer time estimate, in practice that naïve calculation may be inaccurate by as much as seventy-five percent. Consequently, there is a need in the art for a more accurate solution for estimating the time required to transfer large files or large numbers of files between computing environments.
Claims
1. A system comprising: a computing platform having processing hardware and a system memory storing a software code including a trained machine learning (ML) model; the processing hardware configured to execute the software code to: identify a file transfer protocol among a plurality of file transfer protocols for transferring one or more files; determine, using the trained ML model, a test data sample and the file transfer protocol, a plurality of parameters correlated with a time required for transferring the one or more files using the file transfer protocol; identify a covariance among the plurality of parameters; provide, based on the covariance and at least one of the plurality of parameters, an algorithm for transferring the one or more files using the file transfer protocol; perform, using the algorithm, a file transfer simulation of the one or more files using the file transfer protocol; provide, using the file transfer simulation, data pooling parameters for transferring the one or more files; and estimate, based on the file transfer simulation and the data pooling parameters, an elapsed time for transferring the one or more files. ||
10. A method for use by a system including a computing platform having a processing hardware and a system memory storing a software code and a trained machine learning (ML) model, the method comprising: identifying, by the software code executed by the processing hardware, a file transfer protocol among a plurality of file transfer protocols for transferring one or more files; determining, by the software code executed by the processing hardware and using the trained ML model, a test data sample and the file transfer protocol, a plurality of parameters correlated with a time required for transferring the one or more files using the file transfer protocol; identifying, by the software code executed by the processing hardware, a covariance among the plurality of parameters; providing, by the software code executed by the processing hardware based on the covariance and at least one of the plurality of parameters, an algorithm for transferring the one or more files using the file transfer protocol; performing a file transfer simulation, by the software code executed by the processing hardware and using the algorithm, of the one or more files using the file transfer protocol; providing, by the software code executed by the processing hardware and using the file transfer simulation, data pooling parameters for transferring the one or more files; and estimating, by the software code executed by the processing hardware based on the file transfer simulation and the data pooling parameters, an elapsed time for transferring the one or more files.