scholarly journals Hierarchical Data Replication and Service Monitoring Methods in a Scientific Data Grid

2009 ◽  
Vol 8 ◽  
pp. 113-124
Author(s):  
Weizhong Lu ◽  
Yuanchun Zhou ◽  
Kaichao Wu ◽  
Baoping Yan
Keyword(s):  
Data Replication ◽  
Data Grid ◽  
Scientific Data ◽  
Hierarchical Data ◽  
Monitoring Methods ◽  
Service Monitoring

scholarly journals RADAR: Runtime Asymmetric Data-Access Driven Scientific Data Replication

2014 ◽  
pp. 296-313 ◽  
Author(s):  
John Jenkins ◽  
Xiaocheng Zou ◽  
Houjun Tang ◽  
Dries Kimpe ◽  
Robert Ross ◽  
...  
Keyword(s):  
Data Replication ◽  
Data Access ◽  
Scientific Data ◽  
Asymmetric Data

scholarly journals Decentralized replication strategies for P2P based Scientific Data Grid

2008 ◽  
Author(s):  
Azizol Abdullah ◽  
Mohamed Othman ◽  
Hamidah Ibrahim ◽  
Md Nasir Sulaiman ◽  
Abu Talib Othman
Keyword(s):  
Data Grid ◽  
Scientific Data

scholarly journals A four-phase data replication algorithm for data grid

2015 ◽  
Vol 4 (1) ◽  
pp. 163 ◽  
Author(s):  
Alireza Saleh ◽  
Reza Javidan ◽  
Mohammad Taghi FatehiKhajeh
Keyword(s):  
Large Scale ◽  
Data Replication ◽  
Data Grid ◽  
Data Availability ◽  
Access Time ◽  
File Transfer ◽  
System Availability ◽  
Large Scale Data ◽  
Effective Network ◽  
Average Access Time

<p>Nowadays, scientific applications generate a huge amount of data in terabytes or petabytes. Data grids currently proposed solutions to large scale data management problems including efficient file transfer and replication. Data is typically replicated in a Data Grid to improve the job response time and data availability. A reasonable number and right locations for replicas has become a challenge in the Data Grid. In this paper, a four-phase dynamic data replication algorithm based on Temporal and Geographical locality is proposed. It includes: 1) evaluating and identifying the popular data and triggering a replication operation when the popularity data passes a dynamic threshold; 2) analyzing and modeling the relationship between system availability and the number of replicas, and calculating a suitable number of new replicas; 3) evaluating and identifying the popular data in each site, and placing replicas among them; 4) removing files with least cost of average access time when encountering insufficient space for replication. The algorithm was tested using a grid simulator, OptorSim developed by European Data Grid Projects. The simulation results show that the proposed algorithm has better performance in comparison with other algorithms in terms of job execution time, effective network usage and percentage of storage filled.</p>

A review of data replication based on meta-heuristics approach in cloud computing and data grid

2020 ◽  
Vol 24 (19) ◽  
pp. 14503-14530 ◽  
Author(s):  
Najme Mansouri ◽  
Mohammad Masoud Javidi
Keyword(s):  
Cloud Computing ◽  
Data Replication ◽  
Data Grid
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