Francis Y. L. Chin

Efficient parallel algorithms for some graph problems

We study parallel algorithms for a number of graph problems, using the Single Instruction Stream-Multiple Data Stream model. We assume that the processors have access to a common memory and that no memory or data alignment time penalties are incurred. We derive a general time bound for a parallel algorithm that uses <italic>K</italic> processors for finding the connected components of an undirected graph. In particular, an <italic>O</italic>(log<supscrpt>2</supscrpt> <italic>n</italic>) time bound can be achieved using only <italic>K</italic> = <italic>n</italic>⌈<italic>n</italic>/log<supscrpt>2</supscrpt> <italic>n</italic>⌉ processors. This result is optimal in the sense that the speedup ratio is linear with the number of processors used. The algorithm can also be modified to solve a whole class of graph problems with the same time bound and fewer processors than previous parallel methods.

Auditing and Inference Control in Statistical Databases

A statistical database (SDB) may be defined as an ordinary database with the capability of providing statistical information to user queries. The security problem for the SDB is to limit the use of the SDB so(that only statistical information is available and no sequence of queries is sufficient to infer protected information about any individual. When such information is obtained, the SDB is said to be compromised.

Efficient parallel algorithms for a class of graph theoretic problems

In this paper, we present efficient parallel algorithms for the following graph problems: finding the lowest common ancestors for vertex pairs of a directed tree; finding all fundamental cycles, a directed spanning forest, all bridges, all bridge-connected components, all separation vertices, all biconnected components, and testing the biconnectivity of an undirected graph. All these algorithms achieve the

Algorithms for Updating Minimal Spanning Trees

O(\lg ^2 n)

Security in statistical databases for queries with small counts

time bound, with the first two algorithms using

A study on the protection of statistical data bases

n\lceil n /\lg n\rceil

Auditing for secure statistical databases

processors and the remaining algorithms using

The Effectiveness Of Output Modification By Rounding For Protection Of Statistical Data Bases

n\lceil n/\lg ^2 n \rceil

Efficient inference control for range Sum queries

processors. In all cases, our algorithms are better than the previously known algorithms and in most cases reduce the number of processors used by a factor of

An O(n) algorithm for determining a near-optimal computation order of matrix chain products

n\lg n