Weighted Data Replication Strategy for Data Grid Considering Economic Approach
Authors: N. Mansouri, A. Asadi
Abstract:
Data Grid is a geographically distributed environment that deals with data intensive application in scientific and enterprise computing. Data replication is a common method used to achieve efficient and fault-tolerant data access in Grids. In this paper, a dynamic data replication strategy, called Enhanced Latest Access Largest Weight (ELALW) is proposed. This strategy is an enhanced version of Latest Access Largest Weight strategy. However, replication should be used wisely because the storage capacity of each Grid site is limited. Thus, it is important to design an effective strategy for the replication replacement task. ELALW replaces replicas based on the number of requests in future, the size of the replica, and the number of copies of the file. It also improves access latency by selecting the best replica when various sites hold replicas. The proposed replica selection selects the best replica location from among the many replicas based on response time that can be determined by considering the data transfer time, the storage access latency, the replica requests that waiting in the storage queue and the distance between nodes. Simulation results utilizing the OptorSim show our replication strategy achieve better performance overall than other strategies in terms of job execution time, effective network usage and storage resource usage.
Keywords: Data grid, data replication, simulation, replica selection, replica placement.
Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1094277
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[1] A. Folling, C. Grimme, J. Lepping and A. Papaspyrou, ”Robust load delegation in service Grid environments,” IEEE Transactions on Parallel and Distributed Systems, vol. 21, pp. 1304-1316, 2010.
[2] O. Sonmez, H. Mohamed, and D. Epema, "On the benefit of processor coallocation in multicluster Grid systems,” IEEE Transactions on Parallel and Distributed Systems, vol. 21, pp. 778-789, 2010.
[3] Li, H., "Realistic workload modeling and its performance impacts in large-scale Escience Grids,” IEEE Transactions on Parallel and Distributed Systems, vol. 21, pp. 480-493, 2010.
[4] I. Foster and C. Kesselman, "The Grid: blueprint for a new computing infrastructure,” Morgan Kaufmann, 2004.
[5] I. Foster, C. Kesselman and S. Tuecke, "The anatomy of the Grid,” 2001
[6] GriPhyN: The Grid physics network project, 12 July 2010. http://www.griphyn.org.
[7] R.S. Chang and M.S. Hu, "A resource discovery tree using bitmap for Grids,” Future Generation Computer Systems, vol. 26, pp. 29-37, 2010.
[8] J. Wu, X. Xu, P. Zhang and C. Liu "A novel multi-agent reinforcement learning approach for job scheduling in Grid Computing,” Future Generation Computer Systems, vol. 27, pp. 430-439, 2011.
[9] S. Ebadi, and L.M. Khanli, "A new distributed and hierarchical mechanism for service discovery in a Grid environment,” Future Generation Computer Systems, vol. 27, pp. 836-842, 2011.
[10] W. Shih, C.T. Yang and S.S. Tseng, "Using a performance-based SKELETON to implement divisible load applications on Grid Computing environments,” Journal of Information Science and Engineering, vol. 25, pp. 59-81, 2009.
[11] R.S. Chang and H.P. Chang, "A dynamic data replication strategy using access weights in Data Grids,” Journal of Supercomputing, vol. 45 (3), pp. 277-295, 2008.
[12] K. Ranganathan and I. Foster, "Identifying dynamic replication strategies for a high performance Data Grid,” in Proceedings of the Second International Workshop on Grid Computing, pp. 75-86, 2001
[13] M. Tang, B.S. Lee, C.K. Yao and X.Y Tang, "Dynamic replication algorithm for the multi-tier Data Grid,” Future Generation Computer Systems, vol. 21 (5), pp. 775-790, 2005.
[14] M. Shorfuzzaman, P. Graham, R. Eskicioglu, "Adaptive popularity-driven replica placement in hierarchical data grids,” The Journal of Supercomputing, vol. 51, pp. 374–392, 2010.
[15] V. Andronikou, K. Mamouras, K. Tserpes, D. Kyriazis and T. Varvarigou, "Dynamic QoS-aware data replication in Grid environments based on data "importance”,” Future Generation Computer Systems, vol. 28 (3), pp. 544-553, 2012.
[16] M.C. Lee, F.Y. Leu, and Y. Chen, "PFRF: An adaptive data replication algorithm based on startopology Data Grids,” Future Generation Computer Systems, 2011.
[17] N. Saadat, A.M. Rahmani, "PDDRA: A new pre-fetching based dynamic data replication algorithm in Data Grids,” Future Generation Computer Systems, 2011.
[18] J. Taheri, Y.C. Lee, A.Y. Zomaya and H.J. Siegel, "A Bee Colony based optimization approach for simultaneous job scheduling and data replication in Grid environments,” Computers & Operations Research, 2011.
[19] N. Mansouri, G.H. Dastghaibyfard, "A dynamic replica management strategy in Data Grid,” Journal of Network and Computer Applications, 2012.
[20] S.-M.Park, J.-H.Kim, Y.-B.Go and W.-S. Yoon, "Dynamic Grid replication strategy based on internet hierarchy,” in International Workshop on Grid and Cooperative Computing, vol. 1001, pp. 1324-1331, 2003.
[21] K. Sashi and A. Thanamani, "Dynamic replication in a Data Grid using a modified BHR region based algorithm,” Future Generation Computer Systems, vol. 27 (2), pp. 202-210, 2011.
[22] A. Horri, R. Sepahvand, and G.H. Dastghaibyfard, "A hierarchical scheduling and replication strategy,” International Journal of Computer Science and Network Security, vol.8, 2008.
[23] W.H. Bell, D.G. Cameron, L. Capozza, A. Paul Millar, K. Stockinger, F. Zini, "Simulation of Dynamic Grid Replication Strategies in OptorSim,” in Proc. of the ACM/IEEE Workshop on Grid Computing (Grid 2002) 2002.
[24] D.G. Cameron, A.P. Millar, C. Nicholson, R. Carvajal-Schiaffino, F. Zini and K. Stockinger, "Optorsim: A simulation tool for scheduling and replica optimization in Data Grids,” in International Conference for Computing in High Energy and NuclearPhysics (CHEP 2004), 2004.
[25] OptorSim–A Replica Optimizer Simulation: http://edg-wp2.web.cern.ch/edgwp2/ optimization/optorsim.html.
[26] W.H. Bell, D.G. Cameron, R. Carvajal-Schiaffino, A.P. Millar, K. Stockinger, and F. Zini, "Evaluating Scheduling and Replica Optimization Strategies in Data Grid,” IEEE, 2003.