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  4. Optimal replica placement strategy for hierarchical data grid systems
 
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Optimal replica placement strategy for hierarchical data grid systems

Journal
Sixth IEEE International Symposium on Cluster Computing and the Grid, 2006. CCGRID 06
Pages
417-420
Date Issued
2006-05
Date
2006-05
Author(s)
PANGFENG LIU  
Wu J.-J.
DOI
10.1109/CCGRID.2006.76
URI
http://ntur.lib.ntu.edu.tw//handle/246246/200704191001140
https://www.scopus.com/inward/record.uri?eid=2-s2.0-33751107734&doi=10.1109%2fCCGRID.2006.76&partnerID=40&md5=0ee77a6d972501ec541e2194e522265d
Abstract
Grid computing is an important mechanism for utilizing distributed computing resources. These resources are distributed in different geographical locations, but are organized to provide an integrated service. In order to speed up data access efficiency data grid systems replicate essential data in multiple locations, so that a user can access the data from a site in his vicinity. This paper studies replica placement in Data Grid systems, taking into account several important issues described below. First, the replicas should be placed in proper server locations so that the workload on each server is balanced. Second, we choose the optimal number of replicas to balance the data access efficiency, and the expensive maintenance costs for multiple copies of data. Clearly, optimizing access cost of data requests and reducing the cost of replication are two conflicting goals. Finding a good balance between them is a challenging task. We propose efficient algorithms for selecting optimal locations for placing the replicas so that the workload among these replica is balanced. Also when given the data usage from each user site and the maximum workload allowed for each replica server, our algorithm efficiently determines the minimum number of replicas required, as well as their locations. © 2006 IEEE.
SDGs

[SDGs]SDG9

Other Subjects
Algorithms; Computational complexity; Computational methods; Computer software maintenance; Cost accounting; Hierarchical systems; Parallel processing systems; Data grid systems; Distributed computing resources; Grid computing; Maintenance costs; Distributed database systems
Type
journal article
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