Clustering Related Tuples in Databases

Bell, David A.; McErlean, F. J.; Stewart, Paige; Arbuckle, W.

doi:10.1093/comjnl/31.3.253

Cited by 19 publications

(7 citation statements)

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“…On the other hand the results of this study have added to our confidence that the V2 algorithm is superior to Malmquist's original Graph-Collapsing algorithm. While the benchmark we used was of course very limited, it is comparable with several others (e.g., Bell, 1984a;Bell et al 1988. ) Our conclusion is therefore that we should use the Graph-Collapsing algorithms in our design and reorganization tool.…”

Section: Discussionsupporting

confidence: 56%

“…The response-time performance obtained after using each of these was compared with that for the only two published algorithms known to the authors dealing with this problem. We call these algorithm Vl and algorithm V2 and they were compared for performance in the past (Bell, 1984b;Bell, McErlean, Stewart, & Arbuckle 1988). Algorithm Vl is a minor development of Malmquist's algorithm (1978) and V2 is a two-level version as described in Section 2.…”

Section: Sacon (Controlled)mentioning

confidence: 99%

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Application of simulated annealing to clustering tuples in databases

Bell

McErlean

Stewart

et al. 1990

J. Am. Soc. Inf. Sci.

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Techniques for general purpose optimization have been derived from the Metropolis Monte Carlo method of simulating the behavior of particles in substances as they are slowly cooled to form crystals. Simulated Annealing is such a derivative and its value for placement problems (e.g., in circuit board layout design) suggests that it could be advantageously applied to clustering tuples in databases in order to enhance responsiveness to queries. In this article we investigate this issue and compare the performance of this technique with a Graph-Collapsing clustering method which is known to perform very well, in order to gain insights into which approach is better for incorporation in a performanceoriented database design tool. We judge that, whilst the new method does give superior results to the graphbased method in many cases, these improvements are gained at such a very considerable expense of algorithm run time as to rule the new technique out of our consideration as a real world general purpose design tool (but perhaps not for some special-purpose databases).

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Section: Discussionsupporting

confidence: 56%

Section: Sacon (Controlled)mentioning

confidence: 99%

Application of simulated annealing to clustering tuples in databases

Bell

McErlean

Stewart

et al. 1990

J. Am. Soc. Inf. Sci.

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“…where no one method is best for all environments) seems to be the general rule. In, for example, external hashing schemes [16,17], buffer management [18] and conventional database clustering [19] we get the same phenomenon.…”

mentioning

confidence: 72%

“…The linear-time graph collapsing, GC, algorithm [19] proceeds as follows. Each pair of scans is weighted by summing the weights of object pairs in T where one object is on one of the scans and the other object is on the other.…”

Section: The Algorithms Graph Collapsingmentioning

confidence: 99%

Experimental Studies of Heuristic Algorithms for Two Level Object Clustering

Bell

McErlean

1994

Kybernetes

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The clustering of objects in a layered object storage system is by common consent an exceedingly difficult problem. Studies the performance of three heuristic placement algorithms. A series of eight reasonably realistic case studies were used as a benchmark battery, and several hundred experiments were carried out to evaluate results of using the algorithms. Presents the results and the insights gained from the study.

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“…Conventional allocation techniques (such as data stripping/de-clustering [3][4] [5] and data contiguity/clustering [6] [7] [SI) are developed mainly for text and numeric files, which although can be different in sizes, are more or less on the same order. Unfortunately, when applied to multimedia applications, the conventional techniques are inadequate and inefficient.…”

Section: Introductionmentioning

confidence: 99%

Multimedia object modelling and storage allocation strategies for heterogeneous parallel access storage devices in real time multimedia computing systems

Chen

Nwosu

Berra

Proceedings of 1993 IEEE 17th International Computer Software and Applications Conference COMPSAC '93

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The improvements in disk speeds have not kept up with improvements in processor and memory speeds. Conventional storage techniques, in the face of multimedia data, are ineficient and/or inadequate. Here, an efficient multimedia object allocation strategy is presented. We describe a multimedia object model, fhe object and storage device characteristics, and the fragmentation strategy. A bipartite graph approach is used f o r mapping fragments to storage devices and a cost function is used to determine an efficient allocation of an object and t o balance the loads on the devices.

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Clustering Related Tuples in Databases

Cited by 19 publications

References 0 publications

Application of simulated annealing to clustering tuples in databases

Application of simulated annealing to clustering tuples in databases

Experimental Studies of Heuristic Algorithms for Two Level Object Clustering

Multimedia object modelling and storage allocation strategies for heterogeneous parallel access storage devices in real time multimedia computing systems

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