TY - GEN
T1 - Application of association rule mining for replication in scientific data grid
AU - Nine, Md S.Q.Zulkar
AU - Azad, Md Abul Kalam
AU - Abdullah, Saad
AU - Monil, Mohammad Alaul Haque
AU - Zahan, Ibna
AU - Kader, Abdulla Bin
AU - Rahman, Rashedur M.
N1 - Publisher Copyright:
© 2014 IEEE.
PY - 2015/1/28
Y1 - 2015/1/28
N2 - Grid computing is the most popular infrastructure in many emerging field of science and engineering where extensive data driven experiments are conducted by thousands of scientists all over the world. Efficient transfer and replication of these peta-byte scale data sets are the fundamental challenges in Scientific Grid. Data grid technology is developed to permit data sharing across many organizations in geographically disperse locations. Replication of data helps thousands of researchers all over the world to access those data sets more efficiently. Data replication is essential to ensure data reliability and availability across the grid. Replication ensures above mentioned criteria by creating more copies of same data sets across the grid. In this paper, we proposed a data mining based replication to accelerate the data access time. Our proposed algorithm mines the hidden rules of association among different files for replica optimization which proves highly efficient for different access patterns. The algorithm is simulated using data grid simulator, OptorSim, developed by European Data Grid project. Then our algorithm is compared with the existing approaches where it outperforms others.
AB - Grid computing is the most popular infrastructure in many emerging field of science and engineering where extensive data driven experiments are conducted by thousands of scientists all over the world. Efficient transfer and replication of these peta-byte scale data sets are the fundamental challenges in Scientific Grid. Data grid technology is developed to permit data sharing across many organizations in geographically disperse locations. Replication of data helps thousands of researchers all over the world to access those data sets more efficiently. Data replication is essential to ensure data reliability and availability across the grid. Replication ensures above mentioned criteria by creating more copies of same data sets across the grid. In this paper, we proposed a data mining based replication to accelerate the data access time. Our proposed algorithm mines the hidden rules of association among different files for replica optimization which proves highly efficient for different access patterns. The algorithm is simulated using data grid simulator, OptorSim, developed by European Data Grid project. Then our algorithm is compared with the existing approaches where it outperforms others.
KW - Association rule mining
KW - Dynamic Replication
KW - Replica Optimization
KW - Scientific Data Grid
UR - http://www.scopus.com/inward/record.url?scp=84923250347&partnerID=8YFLogxK
U2 - 10.1109/ICECE.2014.7026895
DO - 10.1109/ICECE.2014.7026895
M3 - Conference contribution
AN - SCOPUS:84923250347
T3 - 8th International Conference on Electrical and Computer Engineering: Advancing Technology for a Better Tomorrow, ICECE 2014
SP - 345
EP - 348
BT - 8th International Conference on Electrical and Computer Engineering
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 8th International Conference on Electrical and Computer Engineering, ICECE 2014
Y2 - 20 December 2014 through 22 December 2014
ER -