FIRE: A File Reunion Based Data Replication Strategy for Data Grids

Cloud is an emerging technology that stores the necessary data and electronic form of data is produced in gigantic quantity. It is vital to maintain the efficacy of this data the need of data recovery services is highly essential. Cloud computing is anticipated as the vital foundation for the creation of IT enterprise and it is an impeccable solution to move databases and application software to big data centers where managing data and services is not completely reliable. Our focus will be on the cloud data storage security which is a vital feature when it comes to giving quality service. It should also be noted that cloud environment comprises of extremely dynamic and heterogeneous environment and because of high scale physical data and resources, the failure of data centre nodes is completely normal.Therefore, cloud environment needs effective adaptive management of data replication to handle the indispensable characteristic of the cloud environment. Disaster recovery using cloud resources is an attractive approach and data replication strategy which attentively helps to choose the data files for replication and the strategy proposed tells dynamically about the number of replicas and effective data nodes for replication. Thus, the objective of future algorithm is useful to help users together the information from a remote location where network connectivity is absent and secondly to recover files in case it gets deleted or wrecked because of any reason. Even, time oriented problems are getting resolved so in less time recovery process is executed.

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A hybrid data replication strategy with fuzzy-based deletion for heterogeneous cloud data centers

The Journal of Supercomputing ◽

10.1007/s11227-018-2427-1 ◽

2018 ◽

Vol 74 (10) ◽

pp. 5349-5372 ◽

Cited By ~ 8

Author(s):

N. Mansouri ◽

M. M. Javidi

Keyword(s):

Data Centers ◽

Data Replication ◽

Cloud Data ◽

Replication Strategy ◽

Hybrid Data ◽

Cloud Data Centers ◽

Heterogeneous Cloud

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Predictive File Replication on the Data Grids

Evolving Developments in Grid and Cloud Computing ◽

10.4018/978-1-4666-0056-0.ch005 ◽

2012 ◽

pp. 67-83

Author(s):

ChenHan Liao ◽

Na Helian ◽

Sining Wu ◽

Mamunur M. Rashid

Keyword(s):

Decision Tree ◽

The Other ◽

Resource Usage ◽

Simulation Environment ◽

Data Grids ◽

Access Latency ◽

Replication Strategy ◽

Network Usage ◽

File Replication ◽

Effective Network

Most replication methods either monitor the popularity of files or use complicated functions to calculate the overall cost of whether or not a replication decision or a deletion decision should be issued. However, once the replication decision is issued, the popularity of the files is changed and may have already impacted access latency and resource usage. This article proposes a decision-tree-based predictive file replication strategy that forecasts files’ future popularity based on their characteristics on the Grids. The proposed strategy has shown superb performance in terms of mean job time and effective network usage compared with the other two replication strategies, LRU and Economic under OptorSim simulation environment.

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Data replication strategy with satisfaction of availability, performance and tenant budget requirements

Cluster Computing ◽

10.1007/s10586-018-02899-6 ◽

2019 ◽

Vol 22 (4) ◽

pp. 1199-1210 ◽

Cited By ~ 8

Author(s):

Said Limam ◽

Riad Mokadem ◽

Ghalem Belalem

Keyword(s):

Data Replication ◽

Replication Strategy

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Towards a New Data Replication Management in Cloud Systems

International Journal of Strategic Information Technology and Applications ◽

10.4018/ijsita.2019040101 ◽

2019 ◽

Vol 10 (2) ◽

pp. 1-20

Author(s):

Abdenour Lazeb ◽

Riad Mokadem ◽

Ghalem Belalem

Keyword(s):

Large Scale ◽

Data Replication ◽

Cloud Provider ◽

Large Scale Data ◽

Dynamic Replication ◽

Replication Strategy ◽

Multiple Copies ◽

Cloud Environments ◽

Real Challenge ◽

Scale Data

Applications produce huge volumes of data that are distributed on remote and heterogeneous sites. This generates problems related to access and sharing data. As a result, managing data in large-scale environments is a real challenge. In this context, large-scale data management systems often use data replication, a well-known technique that treats generated problems by storing multiple copies of data, called replicas, across multiple nodes. Most of the replication strategies in these environments are difficult to adapt to cloud environments. They aim to achieve the best performance of the system without meeting the important objectives of the cloud provider. This article proposes a new dynamic replication strategy. The proposed algorithm significantly improves provider gain without neglecting customer satisfaction.

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