2017•Unpublished venueRequires access

Improving the Availability and Reducing Redundancy using Deduplication of Cloud Storage System

Dhanaraj SureshPatil, Rashmi V. Mane, Vijay R. Ghorpade

Open publisher page 3 citations

Abstract

In recent Years, the Growing popularity of cloud storage service has led many organizations and governments to switch their data to cloud storage system; however, using a single cloud storage system provided by different vendors raises some issues like a single point of failure, vendor lock-in problem. In this manner, using multiple cloud vendors known as, a cloud-of-clouds is an effectual way to provide better availability. In this cloud storage system, data is distributed over multiple cloud providers by using one of the data distribution techniques. Mostly for data distribution Replication or erasure code schemes are used. But both techniques have some pros and cons, during replication, multiple copies are created which increases the storage space of cloud systems. As well as in erasure code scheme, files are fragmented into small chunks and those chunks are distributed over cloud while in updating file using this scheme is not so easy. In the proposed system, we merge the pros of both schemes replication and erasure code for data availability and cost efficient system and to avoid redundancy in the data we had used data deduplication technique which also helps to minimize the redundancy of cloud systems.

About this research paper

What this paper is about

In recent Years, the Growing popularity of cloud storage service has led many organizations and governments to switch their data to cloud storage system; however, using a single cloud storage system provided by different vendors raises some issues like a single point of failure, vendor lock-in problem. In this manner, using multiple cloud vendors known as, a cloud-of-clouds is an effectual way to provide better availability. In this cloud storage system, data is distributed over multiple cloud providers by using one of the data distribution techniques. Mostly for data distribution Replication or erasure code schemes are used. But both techniques have some pros and cons, during replication, multiple copies are created which increases the storage space of cloud systems. As well as in erasure code scheme, files are fragmented into small chunks and those chunks are distributed over cloud while in updating file using this scheme is not so easy. In the proposed system, we merge the pros of both schemes replication and erasure code for data availability and cost efficient system and to avoid redundancy in the data we had used data deduplication technique which also helps to minimize the redundancy of cloud systems.

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Available abstract

In recent Years, the Growing popularity of cloud storage service has led many organizations and governments to switch their data to cloud storage system; however, using a single cloud storage system provided by different vendors raises some issues like a single point of failure, vendor lock-in problem. In this manner, using multiple cloud vendors known as, a cloud-of-clouds is an effectual way to provide better availability. In this cloud storage system, data is distributed over multiple cloud providers by using one of the data distribution techniques. Mostly for data distribution Replication or erasure code schemes are used. But both techniques have some pros and cons, during replication, multiple copies are created which increases the storage space of cloud systems. As well as in erasure code scheme, files are fragmented into small chunks and those chunks are distributed over cloud while in updating file using this scheme is not so easy. In the proposed system, we merge the pros of both schemes replication and erasure code for data availability and cost efficient system and to avoid redundancy in the data we had used data deduplication technique which also helps to minimize the redundancy of cloud systems.

Key concepts: Erasure code, Computer science, Cloud storage, Data deduplication, Cloud computing, Vendor, Distributed computing, Data redundancy

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