International Journal of Computer
Trends and Technology

Research Article | Open Access | Download PDF

Volume 1 | Issue 3 | Year 2011 | Article Id. IJCTT-V1I3P115 | DOI : https://doi.org/10.14445/22312803/IJCTT-V1I3P115

GLIP: A Concurrency Control Protocol for Clipping Indexing


J.RAMESH,N.SWATHI,R.LAKSHMI TULASI

Citation :

J.RAMESH,N.SWATHI,R.LAKSHMI TULASI, "GLIP: A Concurrency Control Protocol for Clipping Indexing," International Journal of Computer Trends and Technology (IJCTT), vol. 1, no. 3, pp. 316-320, 2011. Crossref, https://doi.org/10.14445/22312803/IJCTT-V1I3P115

Abstract

The project Concurrency Control Protocol for Clipping Indexing deals with the multidimensional databases. In multidimensional indexing trees, the overlapping of nodes will tend to degrade query performance, as one single point query may need to traverse multiple branches of the tree if the query point is in an overlapped area. Multidimensional databases are beginning to be used in a wide range of applications. To meet this fast-growing demand, the R-tree family is being applied to support fast access to multidimensional data, for which the R+-tree exhibits outstanding search performance. In order to support efficient concurrent access in multiuser environments, concurrency control mechanisms for multidimensional indexing have been proposed. However, these mechanisms cannot be directly applied to the R+-tree because an object in the R+-tree may be indexed in multiple leaves. This paper proposes a concurrency control protocol for R-tree variants with object clipping, namely, Granular Locking for clipping indexing (GLIP). GLIP is the first concurrency control approach specifically designed for the R+-tree and its variants, and it supports efficient concurrent operations with serializable isolation, consistency, and deadlock-free. Experimental tests on both real and synthetic data sets validated the effectiveness and efficiency of the proposed concurrent access framework.

Keywords

Concurrency, indexing methods, spatial databases.

References

[1] K. Chakrabarti and S. Mehrotra, “Dynamic Granular Locking Approach to Phantom Protection in R-Trees,” Proc. 14th IEEE Int’l Conf. Data Eng. (ICDE ’98), pp. 446-454, 1998.
[2] K. Chakrabarti and S. Mehrotra, “Efficient Concurrency Control in Multi-Dimensional Access Methods,” Proc. ACM SIGMOD ’99, pp. 25-36, 1999.
[3] J.K. Chen, Y.F. Huang, and Y.H. Chin, “A Study of Concurrent Operations on R-Trees,” Information Sciences, vol. 98, nos. 1-4, pp. 263- 300, May 1997.
[4] V. Gaede and O. Gunther, “Multidimensional Access Methods,” ACM Computing Surveys, vol. 30, no. 2, pp. 170-231, June 1998.
[5] D. Greene, “An Implementation and Performance Analysis of Spatial Data AccessMethods,” Proc. Fifth IEEE Int’l Conf. Data Eng. (ICDE ’89), pp. 606-615, 1989.
[6] S. Guha, R. Rastogi, and K. Shim, “CURE: An Efficient Clustering Algorithm for Large Databases,” Proc. ACM SIGMOD ’98, pp. 73-84, 1998.
[7] A. Guttman, “R-Trees: A Dynamic Index Structure for Spatial Searching,” Proc. ACM SIGMOD ’84, pp. 47-57, 1984.
[8] D. Greene, “An Implementation and Performance Analysis of Spatial Data AccessMethods,” Proc. Fifth IEEE Int’l Conf. Data Eng. (ICDE ’89), pp. 606-615, 1989.
[9] S. Guha, R. Rastogi, and K. Shim, “CURE: An Efficient Clustering Algorithm for Large Databases,” Proc. ACM SIGMOD ’98, pp. 73-84, 1998.
[10] A. Guttman, “R-Trees: A Dynamic Index Structure for Spatial Searching,” Proc. ACM SIGMOD ’84, pp. 47-57, 1984.