DDEAS: Distributed Deduplication System with Efficient Access in Cloud Data Storage
Bhavya M1, Thriveni J2, Venugopal K R3
1Bhavya M, Department of Computer Science and Engineering UniversityVisvesvaraya College of Engineering Bengaluru, India
2ThriveniJ, Department of Computer Science and Engineering University Visvesvaraya College of Engineering Bengaluru, India.
3Venugopal K R, Vice Chancellor Banglore University, Bengaluru, India.
Manuscript received on November 22, 2019. | Revised Manuscript received on December 15, 2019. | Manuscript published on December 30, 2019. | PP: 1943-1949 | Volume-9 Issue-2, December, 2019. | Retrieval Number: B2900129219/2019©BEIESP | DOI: 10.35940/ijeat.B2900.129219
Open Access | Ethics and Policies | Cite | Mendeley
© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Cloud storage service is one of the vital function of cloud computing that helps cloud users to outsource a massive volume of data without upgrading their devices. However, cloud data storage offered by Cloud Service Providers (CSPs) faces data redundancy problems. The data de-duplication technique aims to eliminate redundant data segments and keeps a single instance of the data set, even if similar data set is owned by any number of users. Since data blocks are distributed among the multiple individual servers, the user needs to download each block of the file before reconstructing the file, which reduces the system efficiency. We propose a server level data recover module in the cloud storage system to improve file access efficiency and reduce network bandwidth utilization time. In the proposed method, erasure coding is used to store blocks in distributed cloud storage and The MD5 (Message Digest 5) is used for data integrity. Executing recover algorithm helps user to directly fetch the file without downloading each block from the cloud servers. The proposed scheme improves the time efficiency of the system and quick access ability to the stored data. Thus consumes less network bandwidth and reduces user processing overhead while data file is downloading.
Keywords: Access Efficiency, Cloud Data storage, Data Deduplication, Network Bandwidth, Recovery module.