The IUP Journal of Computer Sciences
Cloud Computing for MATLAB and R Users:
Part II – Transferring Data and Cloud Storage

Article Details
Pub. Date : April, 2019
Product Name : The IUP Journal of Computer Sciences
Product Type : Article
Product Code : IJCS11904
Author Name : Michael Gallagher, Erick Rengifo and Rossen Trendafilov
Availability : YES
Subject/Domain : Management
Download Format : PDF Format
No. of Pages : 24



Cloud-based computing has tremendous potential for academia in general and researchers in particular. The ability to store, read and manipulate large dataset is increasingly important to be on the cutting-edge of research. While most researchers have extensive programming skills, they generally are not computer scientists. A number of cloud-based, virtual work spaces have been developed which can bring enormous computing advantages over any desktop or laptop. However, the instructions to get up and running in the cloud are often overwhelming, and require a significant investment of time.


If the data file that the researcher is using is not large, he can save the file on his own computer and upload it to the instance whenever it is needed. In the same way, his output files can be easily downloaded back to his computer. However, if the data files are very large, a better option for users is to upload their data to AWS cloud storage (S3) and then transfer it, whenever needed, to EC2 for analysis and later save the results back to S3.


Interactivity, ProgrammingCloud computing, Amazon Web Services (AWS), S3, Elastic Compute Cloud (EC2), Virtual computing instance, Linux R, MATLAB