This paper is published in Volume-8, Issue-3, 2022
Area
CSE
Author
B. Akhil Kumar, Dr. T. Uma Devi
Org/Univ
Gandhi Institute of Technology and Management, Visakhapatnam, Andhra Pradesh, India
Pub. Date
06 June, 2022
Paper ID
V8I3-1379
Publisher
Keywords
AWS S3 Bucket, Huffman Compression Algorithm, LZW Compression Algorithm, File Management

Citationsacebook

IEEE
B. Akhil Kumar, Dr. T. Uma Devi. Efficient cloud data storage and file management using AWS S3 bucket, International Journal of Advance Research, Ideas and Innovations in Technology, www.IJARIIT.com.

APA
B. Akhil Kumar, Dr. T. Uma Devi (2022). Efficient cloud data storage and file management using AWS S3 bucket. International Journal of Advance Research, Ideas and Innovations in Technology, 8(3) www.IJARIIT.com.

MLA
B. Akhil Kumar, Dr. T. Uma Devi. "Efficient cloud data storage and file management using AWS S3 bucket." International Journal of Advance Research, Ideas and Innovations in Technology 8.3 (2022). www.IJARIIT.com.

Abstract

In the world of IT, end-user data is considered to be the basis of everything. A huge amount of data is added every day to the system and a far greater amount of data is being modified every second. Everyone expects that storing of data should be on the go and that their data should be safe and secure. While keeping the data secure, the procurement of the same should be seamless and fast. To serve this purpose, one of the dominant and reliable, technologies of the 20th century has been provided by one of the many products of Amazon Web Services by the name of Simple Storage Service(S3) that can store and retrieve huge amounts of data from any form of application, be it web-based or mobile, at an incredible speed. The data stored in S3 uses a flat-file system that is easy to understand and implement. Amazon S3 (Simple Storage Service) provides object storage, that is built for storing and recovering any amount of information or data from anywhere over the internet. It provides this storage through a web services interface. It can also store different file formats up to 5 terabytes in size. The scope of this project is to establish easy upload/retrieval of files from AWS S3 storage using different compression techniques and perform file operations on it. This way, one will be able to check which compression technique works efficiently in terms of compressed data size and also if the original data or file is corrupted, compromised, or destroyed, a backup is available on the cloud to recover. The proposed methodology also targets a few of the limitations of the flat file system of AWS S3 and provides a solution in the form of directory structure which on implementation can result in more security and can tackle inconsistency even for huge databases.