A replica placement and replacement algorithm for data-grid in DRTDBS

Author(s):  
S. K. Singh ◽  
A. Prasad ◽  
P. K. Singh ◽  
R. K. Singh
Author(s):  
Ghalem Belalem

Data grids have become an interesting and popular domain in grid community (Foster and Kesselmann, 2004). Generally, the grids are proposed as solutions for large scale systems, where data replication is a well-known technique used to reduce access latency and bandwidth, and increase availability. In splitting of the advantages of replication, there are many problems that should be solved such as, • The replica placement that determines the optimal locations of replicated data in order to reduce the storage cost and data access (Xu et al, 2002); • The problem of determining which replica will be accessed to in terms of consistency when we need to execute a read or write operation (Ranganathan and Foster, 2001); • The problem of degree of replication which consists in finding a minimal number of replicas without reducing the performance of user applications; • The problem of replica consistency that concerns the consistency of a set of replicated data. This consistency provides a completely coherent view of all the replicas for a user (Gray et al 1996). Our principal aim, in this article, is to integrate into consistency management service, an approach based on an economic model for resolving conflicts detected in the data grid.


Fuzzy Systems ◽  
2017 ◽  
pp. 516-539
Author(s):  
Nazanin Saadat ◽  
Amir Masoud Rahmani

One of the challenges of data grid is to access widely distributed data fast and efficiently and providing maximum data availability with minimum latency. Data replication is an efficient way used to address this challenge by replicating and storing replicas, making it possible to access similar data in different locations of the data grid and can shorten the time of getting the files. However, as the number and storage size of grid sites is limited and restricted, an optimized and effective replacement algorithm is needed to improve the efficiency of replication. In this paper, the authors propose a novel two-level replacement algorithm which uses Fuzzy Replica Preserving Value Evaluator System (FRPVES) for evaluating the value of each replica. The algorithm was tested using a grid simulator, OptorSim developed by European Data Grid projects. Results from simulation procedure show that the authors' proposed algorithm has better performance in comparison with other algorithms in terms of job execution time, total number of replications and effective network usage.


2013 ◽  
Vol 5 (1) ◽  
pp. 70-81 ◽  
Author(s):  
Mohammed K. Madi ◽  
Yuhanis Yusof ◽  
Suhaidi Hassan

Data Grid is an infrastructure that manages huge amount of data files, and provides intensive computational resources across geographically distributed collaboration. To increase resource availability and to ease resource sharing in such environment, there is a need for replication services. Data replication is one of the methods used to improve the performance of data access in distributed systems by replicating multiple copies of data files in the distributed sites. Replica placement mechanism is the process of identifying where to place copies of replicated data files in a Grid system. Existing work identifies the suitable sites based on number of requests and read cost of the required file. Such approaches consume large bandwidth and increases the computational time. The authors propose a replica placement strategy (RPS) that finds the best locations to store replicas based on four criteria, namely, 1) Read Cost, 2) File Transfer Time, 3) Sites’ Workload, and 4) Replication Sites. OptorSim is used to evaluate the performance of this replica placement strategy. The simulation results show that RPS requires less execution time and consumes less network usage compared to existing approaches of Simple Optimizer and LFU (Least Frequently Used).


2007 ◽  
Vol 6 (1) ◽  
pp. 103-123 ◽  
Author(s):  
Rashedur M. Rahman ◽  
Ken Barker ◽  
Reda Alhajj
Keyword(s):  

2011 ◽  
Vol 84 (7) ◽  
pp. 1224-1232 ◽  
Author(s):  
Zhihui Du ◽  
Jingkun Hu ◽  
Yinong Chen ◽  
Zhili Cheng ◽  
Xiaoying Wang
Keyword(s):  

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