Data Chunks Placement Optimization for Hybrid Storage Systems
“Hybrid Cloud Storage” (HCS) is a widely adopted framework that combines the functionality of public and private cloud storage models to provide storage services. This kind of storage is especially ideal for organizations that seek to reduce the cost of their storage infrastructure with the use of “...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2021-07-01
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| Series: | Future Internet |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1999-5903/13/7/181 |
| _version_ | 1797527116094373888 |
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| author | Agil Yolchuyev Janos Levendovszky |
| author_facet | Agil Yolchuyev Janos Levendovszky |
| author_sort | Agil Yolchuyev |
| collection | DOAJ |
| description | “Hybrid Cloud Storage” (HCS) is a widely adopted framework that combines the functionality of public and private cloud storage models to provide storage services. This kind of storage is especially ideal for organizations that seek to reduce the cost of their storage infrastructure with the use of “Public Cloud Storage” as a backend to on-premises primary storage. Despite the higher performance, the hybrid cloud has latency issues, related to the distance and bandwidth of the public storage, which may cause a significant drop in the performance of the storage systems during data transfer. This issue can become a major problem when one or more private storage nodes fail. In this paper, we propose a new framework for optimizing the data uploading process that is currently used with hybrid cloud storage systems. The optimization is concerned with spreading the data over the multiple storages in the HCS system according to some predefined objective functions. Furthermore, we also used Network Coding technics for minimizing data transfer latency between the receiver (private storages) and transmitter nodes. |
| first_indexed | 2024-03-10T09:39:27Z |
| format | Article |
| id | doaj.art-9fa4e1900c89436095b66d95f25a7be1 |
| institution | Directory Open Access Journal |
| issn | 1999-5903 |
| language | English |
| last_indexed | 2024-03-10T09:39:27Z |
| publishDate | 2021-07-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Future Internet |
| spelling | doaj.art-9fa4e1900c89436095b66d95f25a7be12023-11-22T03:50:24ZengMDPI AGFuture Internet1999-59032021-07-0113718110.3390/fi13070181Data Chunks Placement Optimization for Hybrid Storage SystemsAgil Yolchuyev0Janos Levendovszky1Department of Networked Systems and Services, Budapest University of Technology and Economics, Magyar Tudosok krt. 2, 1117 Budapest, HungaryDepartment of Networked Systems and Services, Budapest University of Technology and Economics, Magyar Tudosok krt. 2, 1117 Budapest, Hungary“Hybrid Cloud Storage” (HCS) is a widely adopted framework that combines the functionality of public and private cloud storage models to provide storage services. This kind of storage is especially ideal for organizations that seek to reduce the cost of their storage infrastructure with the use of “Public Cloud Storage” as a backend to on-premises primary storage. Despite the higher performance, the hybrid cloud has latency issues, related to the distance and bandwidth of the public storage, which may cause a significant drop in the performance of the storage systems during data transfer. This issue can become a major problem when one or more private storage nodes fail. In this paper, we propose a new framework for optimizing the data uploading process that is currently used with hybrid cloud storage systems. The optimization is concerned with spreading the data over the multiple storages in the HCS system according to some predefined objective functions. Furthermore, we also used Network Coding technics for minimizing data transfer latency between the receiver (private storages) and transmitter nodes.https://www.mdpi.com/1999-5903/13/7/181cloud computingcloud storagesoptimization algorithmsnetwork coding |
| spellingShingle | Agil Yolchuyev Janos Levendovszky Data Chunks Placement Optimization for Hybrid Storage Systems Future Internet cloud computing cloud storages optimization algorithms network coding |
| title | Data Chunks Placement Optimization for Hybrid Storage Systems |
| title_full | Data Chunks Placement Optimization for Hybrid Storage Systems |
| title_fullStr | Data Chunks Placement Optimization for Hybrid Storage Systems |
| title_full_unstemmed | Data Chunks Placement Optimization for Hybrid Storage Systems |
| title_short | Data Chunks Placement Optimization for Hybrid Storage Systems |
| title_sort | data chunks placement optimization for hybrid storage systems |
| topic | cloud computing cloud storages optimization algorithms network coding |
| url | https://www.mdpi.com/1999-5903/13/7/181 |
| work_keys_str_mv | AT agilyolchuyev datachunksplacementoptimizationforhybridstoragesystems AT janoslevendovszky datachunksplacementoptimizationforhybridstoragesystems |