This Article 
 Bibliographic References 
 Add to: 
Practically Realizable Efficient Data Allocation and Replication Strategies for Distributed Databases with Buffer Constraints
September 2006 (vol. 17 no. 9)
pp. 1001-1013

Abstract—In this paper, we address the performance of distributed database systems with buffer constraints. Specifically, our objective is to design and analyze efficient data allocation and replication strategies to minimize the total servicing cost for an arbitrary read/write request sequence, under finite buffer constraints of the nodes in the system. When the available buffer space in a node is not enough to store a copy of an object, the decision has to be made on whether or not we should evict one or more objects in use to give room for the new object copy. In this paper, we design and analyze the data replication strategies with the model of Dynamic Window Mechanism (DWM) algorithm jointly implemented with different types of object replacement strategies (No Replacement, LRU, and LFU) commonly found in practice. We consider situations wherein the object sizes are identical as well as heterogeneous. We will show the impact on the performance of the allocation and replication strategies due to the limited local database buffer capacities. We analyze and quantify theoretically (using competitive analysis) the performances of all the proposed algorithms. Further, we perform rigorous simulation experiments to validate the findings with respect to several influencing parameters. Several useful conclusions are drawn based on the experimental results and we highlight the usefulness of the algorithms under different situations.

[1] P.K. Reddy and S. Bhalla, “Asynchronous Operations in Distributed Concurrency Control,” IEEE Trans. Knowledge and Data Eng., vol. 15, no. 3, pp. 721-733, May-June 2003.
[2] W. Lin and B. Veeravalli, Object Management in Distributed Database Systems for Stationary and Mobile Computing Environments: A Competitive Approach, Network Theory and Applications Series, vol. 12, Kluwer Academic, 2003.
[3] J. Yoon, S.L. Min, and Y. Cho, “Buffer Cache Management: Predicting the Future from the Past,” Proc. Int'l Symp. Parallel Architectures, Algorithms and Networks (ISPAN '02), pp. 92-97, May 2002.
[4] S.A. Cook, J.K. Pachl, and I.S. Pressman, “The Optimal Location of Replicas in a Network Using a Read-One-Write-All Policy,” Distributed Computing, vol. 15, no. 1, pp. 57-66, Apr. 2002.
[5] K. Hazelwood and M.D. Smith, “Code Cache Management Schemes for Dynamic Optimizers,” Proc. Workshop Interaction between Compilers and Computer Architecture (Interact-6), Feb. 2002.
[6] A.S. Tanenbaum and M. Van Steen, Distributed Systems: Principles and Paradigms. Prentice Hall, 2002.
[7] P. Verissimo and L. Rodrigues, Distributed Systems for System Architects. Kluwer Academic Publishers, 2001.
[8] K. Kalpakis, K. Dasgupta, and O. Wolfson, “Optimal Placement of Replicas in Trees with Read, Write, and Storage Costs,” IEEE Trans. Parallel and Distributed Systems, vol. 12, no. 6, pp. 628-637, June 2001.
[9] G.F. Johnson and A.K. Singh, “Stable and Fault-Tolerant Object Allocation,” Proc. 19th Ann. ACM Symp. Principles of Distributed Computing, pp. 259-268, July 2000.
[10] S. Jin and A. Bestavros, “Popularity-Aware GreedyDual-Size Web Proxy Caching Algorithms,” Proc. Int'l Conf. Distributed Computing Systems (ICDCS '00), pp. 254-261, Apr. 2000.
[11] T.M. Ozsu and P. Valduriez, Principles of Distributed Database Systems, P. Valduriez, ed., Prentice Hall, 1999.
[12] O. Wolfson and Y. Huang, “Competitive Analysis of Caching in Distributed Databases,” IEEE Trans. Parallel and Distributed Systems, vol. 9, no. 4, pp. 391-409, Apr. 1998.
[13] A. Borodin and R. El-Yaniv, “Online Computation and Competitive Analysis,” New York: Cambridge Univ. Press, 1998.
[14] L. Rizzo and L. Vicisano, “Replacement Policies for a Proxy Cache,” Technical Report, rn/98/13, Dept. of Computer Science, Univ. College London, 1998.
[15] O. Wolfson, S. Jajodia, and Y. Huang, “An Adaptive Data Replication Algorithm,” ACM Trans. Database Systems, vol. 22, no. 2, pp. 255-314, 1997.
[16] H. Xu, T. Furukawa, and Y. Shi, “Concurrency Control Based on Order Constraints in Advanced Database Systems,” Proc. Int'l Symp. Cooperative Database Systems for Advanced Applications (CODAS), pp. 380-385, 1997.
[17] S. Albers, “Competitive Online Algorithms,” Basic Research in Computer Science, LS-96-2, LSSN 1295-2048, Sept. 1996.
[18] R. Karedla, J.S. Love, and B.G. Wheery, “Caching Strategies to Improve Disk System Performance,” Computer, vol. 27, no. 3, pp. 38-46, Mar. 1994.
[19] Y. Huang and O. Wolfson, “A Competitive Dynamic Data Replication Algorithm,” Proc. IEEE Ninth Int'l Conf. Data Eng. '93, pp. 310-317, 1993.
[20] K. Hwang, Advanced Computer Architecture: Parallelism, Scalability, Programmability. McGraw-Hill, 1993.
[21] E.J. O'Neil, P.E. O'Neil, and G. Weikum, “The LRU-K Page Replacement Algorithm for Database Disk Buffering,” Proc. ACM SIGMOD Int'l Conf. Management of Data, pp. 297-306, 1993.
[22] B. Awerbuch, Y. Bartal, and A. Fiat, “Competitive Distributed File Allocation,” Proc. 25th ACM Symp. Theory of Computing, pp. 164-173, May 1993.
[23] O. Wolfson and S. Jajodia, “Distributed Algorithms for Dynamic Replication of Data,” Proc. 11th ACM Symp. Principles of Database Systems, pp. 149-163, June 1992.
[24] O. Wolfson and S. Jajodia, “An Algorithm for Dynamic Data Distribution,” Proc. Second Workshop Management of Replicated Data (WMRD-II), pp. 62-65, 1992.
[25] O. Wolfson and A. Milo, “The Multicast Policy and Its Relationship to Replicated Data Placement,” ACM TODS, vol. 16, no. 1, 1991.
[26] D.D. Sleator and R.E. Tarjan, “Amortized Efficiency of List Update and Paging Rules,” Comm. ACM, vol. 28, no. 2, pp. 202-208, 1985.

Index Terms:
Object allocation, distributed database system, competitiveness, replacement algorithms, caching, communication cost.
Xin Gu, Wujuan Lin, Bharadwaj Veeravalli, "Practically Realizable Efficient Data Allocation and Replication Strategies for Distributed Databases with Buffer Constraints," IEEE Transactions on Parallel and Distributed Systems, vol. 17, no. 9, pp. 1001-1013, Sept. 2006, doi:10.1109/TPDS.2006.127
Usage of this product signifies your acceptance of the Terms of Use.