High-Performance Parallel Database Processing and Grid Databases- P13

High-Performance Parallel Database Processing and Grid Databases- P13: Parallel databases are database systems that are implemented on parallel computingplatforms. Therefore, high-performance query processing focuses on queryprocessing, including database queries and transactions, that makes use of parallelismtechniques applied to an underlying parallel computing platform in order toachieve high performance.
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High-Performance Parallel Database Processing and Grid Databases- P13 BIBLIOGRAPHY 531Coulon, C., Pacitti, E., and Valduriez, P., “Consistency Management for Partial Replication in a High Performance Database Cluster”, Proceedings of International Conference on Parallel and Distributed Systems (ICPADS), pp. 809–815, 2005.Dullmann, D., Hosckek, W., Jaen-Martinez, J., Segal, B., Samar, A., Stockinger, H., and Stockinger, K., “Models for Replica Synchronisation and Consistency in a Data Grid”, Proceedings of 10th IEEE International Symposium on High Performance and Distributed Computing (HPDC), pp. 67–75, August 2001.Honicky, R.J. and Miller, E.L., “A Fast Algorithm for Online Placement and Reorganization of Replicated Data”, Proceedings of International Parallel and Distributed Processing Symposium (IPDPS), pp. 57, 2003.Huang, C., Xu, F., and Hu, X., “Massive Data Oriented Replication Algorithms for Consis- tency Maintenance in Data Grids”, Proceedings of International Conference on Compu- tational Science, pp. 838–841, 2006.Lamehamedi, H., Shentu, Z., Szymanski, B.K., and Deelman, E., “Simulation of Dynamic Data Replication Strategies in Data Grids”, Proceedings of International Parallel and Distributed Processing Symposium (IPDPS), pp. 100, 2003.Lei, M. and Vrbsky, S.V., “A Data Replication Strategy to Increase Data Availability in Data Grids”, Proceedings of the International Conference on Grid Computing & Applications (GCA), pp. 221–227, 2006.Lin, Y., Liu, P., and Wu, J., “Optimal Placement of Replicas in Data Grid Environments with Locality Assurance”, Proceedings of International Conference on Parallel and Dis- tributed Systems (ICPADS), pp. 465–474, 2006.Liu, P. and Wu, J., “Optimal Replica Placement Strategy for Hierarchical Data Grid Sys- tems”, Proceedings of Cluster Computing and the Grid (CCGRID), pp. 417–420, 2006.Park, S., Kim, J., Ko, Y., and Yoon, W., “Dynamic Data Grid Replication Strategy Based on Internet Hierarchy”, Proceedings of Grid and Cooperative Computing (GCC), pp. 838–846, 2003.Rahman, R.M., Barker, K., and Alhajj, R., “Replica Placement in Data Grid: A Multi-objective Approach”, Proceedings of Grid and Cooperative Computing (GCC), pp. 645–656, 2005.Ranganathan, K. and Foster, I.T., “Identifying Dynamic Replication Strategies for a High-Performance Data Grid”, Proceedings of International Workshop on Grid Computing (GRID), pp. 75–86, 2001.Sithole, E., Parr, G.P., and McClean, S.I., “Data grid performance analysis through study of replication and storage infrastructure parameters”, Proceedings of Cluster Computing and the Grid (CCGRID), pp. 293–300, 2005.Stockinger, H., Samar, A., Holtman, K., Allcock, W.E., Foster, I.T., and Tierney, B., “File and Object Replication in Data Grids”, Proceedings of IEEE International Symposium on High Performance Distributed Computing (HPDC), pp. 76–86, 2001.Tang, M., Lee, B., Tang, X., and Yeo, C.K., “Combining Data Replication Algorithms and Job Scheduling Heuristics in the Data Grid”, Proceedings of Euro-Par, pp. 381–390, 2005.Tao, J. and Williams, J., “Concurrency Control and Data Replication Strategies for Large-scale and Wide-distributed Databases”, Proceedings of Database Systems for Advanced Applications (DASFAA), 2001.Vazhkudai, S., Tuecke, S., and Foster, I., “Replica Selection in the Globus Data Grid”, Proceedings of the 1st IEEE/ACM International Conference on Cluster Computing and the Grid (CCGrid), pp. 106–113, May 2001.532 BIBLIOGRAPHYYou, X., Chang, G., Chen, X., Tian, C., and Zhu, C., “Utility-Based Replication Strategies in Data Grids”, Proceedings of Grid and Cooperative Computing (GCC), pp. 500–507, 2006.CHAPTER 15: PARALLEL OLAP AND BUSINESSINTELLIGENCEAkal, F., Böhm, K., and Schek, H., “OLAP Query Evaluation in a Database Cluster: A Performance Study on Intra-Query Parallelism”, Proceedings of Advances in Databases and Information Systems (ADBIS), pp. 218–231, 2002.Azharul Hasan, K.M., Tsuji, T., and Higuchi, K., “A Parallel Implementation Scheme of Relational Tables Based on Multidimensional Extendible Array”, International Journal of Data Warehousing and Mining, 2(4):66–85, 2006.Chen, Y., Dehne, F., Eavis, T., and Rau-Chaplin, A., “Building Large ROLAP Data Cubes in Parallel”, Proceedings of International Database Engineering and Application Sym- posium (IDEAS), pp. 367–377, 2004.Chen, Y., Dehne, F., Eavis, T., and Rau-Chaplin, A., “Improved data partitioning for build- ing large ROLAP data cubes in parallel”, Journal of Data Warehousing and Mining, 2(1):1–26, 2006.Chen, Y., Dehne, F., Eavis, T., and Rau-Chaplin, A., “Parallel ROLAP Data Cube Con- struction On Shared-Nothing Multiprocessors”, Proceedings of International Parallel and Distributed Processing Symposium ...