DESIGNING FAULT-TOLERANT DATA STORAGE SYSTEMS WITH ERASURE CODING IN GEO-DISTRIBUTED CLOUD ENVIRONMENTS

DESIGNING FAULT-TOLERANT DATA STORAGE SYSTEMS WITH ERASURE CODING IN GEO-DISTRIBUTED CLOUD ENVIRONMENTS

Registration ID: IJNRD_227141

Published ID: IJNRD2408414

DOI: Click Here to Get

Pranav Murthy , Dheerender Thakur

Fault Tolerance, Erasure Coding, Geo-Distributed Cloud, Data Storage Systems

This work aims to create and assess a fault-tolerant data storage architecture applied to systems based on erasure coding in geo-distributed clouds. Distributed storage in cloud environments has limitations concerning data duplication, effectiveness, and reliability, referencing geo-distributed data storage. This research will address these issues by incorporating erasure coding into the storage building blocks. The proposed system employs erasure coding for redundancy and fault tolerance. The project entails the creation of a representation plan that would allow us to place data in a geo-distributed manner in the cloud storage with fault tolerance for failure, in other words, the ability to avoid data loss in case of failures. Optimized erasure coder techniques, which include Reed Solomons and LRC, are used to disseminate data. The geo-distribution option entails the spread of data to different regions in the Cloud and or both in the private or public Cloud. Simulations and actual tests assess the system's capability regarding data retrieval, storage capacity, and fault recovery time. The results show that the proposed system presents a 40% enhancement in fault tolerance compared to replication techniques, where data loss during failures is common. Further, it has a 30% storage overhead compared to the conventional procedure, making the system more storage efficient. Some other measurements in the context of the Hadoop system include Data retrieval times, which have turned out to be a 20 percent enhancement compared to current systems. Fault tolerance, storage utilization, response time regarding data access, and the time taken to reconstruct failed databases were the metrics used with giant leaps ahead of baseline models. This study shows that extending erasure coding into geo-distributed cloud storage systems can improve network resilience and storage capacity. This approach provides a feasible solution to the CSPs looking to increase the DR in multiple geo-regional installations. The research also provides grounds for further studying how optimizing erasure coding schemes for large-scale cloud environments could be possible. Future work can focus on the extension of automatically adapting the erasure coding parameters according to the current network status and storage requirements using the machine learning approach.

Published Paper   E-Certificate

"DESIGNING FAULT-TOLERANT DATA STORAGE SYSTEMS WITH ERASURE CODING IN GEO-DISTRIBUTED CLOUD ENVIRONMENTS", IJNRD - INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT (www.IJNRD.org), ISSN:2456-4184, Vol.9, Issue 8, page no.e149-e161, August-2024, Available :https://ijnrd.org/papers/IJNRD2408414.pdf

Volume 9 Issue 8, August-2024

Pages : e149-e161

Paper Reg. ID: IJNRD_227141

Published Paper Id: IJNRD2408414

Downloads: 000121180

Research Area: Engineering

Country: -, -, India

Published Paper PDF: https://ijnrd.org/papers/IJNRD2408414.pdf

Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2408414

Journal Name: INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT(IJNRD)

ISSN: 2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar | ESTD YEAR: 2016

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.76 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

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This work is licensed under a Creative Commons Attribution 4.0 International License and The Open Definition

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