7468422
On Containment of Conjunctive Queries with Arithmetic Comparisons
We study the following problem: how to test if Q 2 is contained in Q 1 , where Q 1 and Q 2 are conjunctive queries with arithmetic comparisons? This problem is fundamental in a large variety of database applications. Existing algorithms first normalize the queries, then test a logical implication using multiple containment mappings from Q 1 to Q 2 . We are interested in cases where the containment can be tested more efficiently. This work aims to (a) reduce the problem complexity from Π P 2-completeness to NP-completeness in these cases; (b) utilize the advantages of the homomorphism property (i.e., the containment test is based on a single containment mapping) in applications such as those of answering queries using views; and (c) observing that many real queries have the homomorphism property. The following are our results. (1) We show several cases where the normalization step is not needed, thus reducing the size of the queries and the number of containment mappings. (2) We develop an algorithm for checking various syntactic conditions on queries, under which the homomorphism property holds. (3) We further reduce the conditions of these classes using practical domain knowledge that is easily obtainable. (4) We conducted experiments on real queries, and show that most of the queries pass this test.
7967297
2D BubbleUp: Managing Parallel Disks for Media Servers
In this study we present a scheme called two-dimensional BubbleUp (2DB) for managing parallel disks in a multimedia server. Its goal is to reduce initial latency for interactive multimedia applications, while balancing disk loads to maintain high throughput. The 2DB scheme consists of a data placement and a request scheduling policy. The data placement policy replicates frequently accessed data and places them cyclically throughout the disks. The request scheduling policy attempts to maintain free ``service slots'''' in the immediate future. These slots can then be used to quickly service newly arrived requests. Through examples and simulation, we show that our scheme significantly reduces initial latency and maintains throughput comparable to that of the traditional schemes.
8510271
Supporting Efficient Record Linkage for Large Data Sets Using Mapping Techniques
This paper describes an efficient approach to record linkage. Given two lists of records, the record-linkage problem consists of determining all pairs that are similar to each other, where the overall similarity between two records is defined based on domain-specific similarities over individual attributes. The record-linkage problem arises naturally in the context of data cleansing that usually precedes data analysis and mining. Since the scalability issue of record linkage was addressed in [21], the repertoire of database techniques dealing with multidimensional data sets has significantly increased. Specifically, many effective and efficient approaches for distance-preserving transforms and similarity joins have been developed. Based on these advances, we explore a novel approach to record linkage. For each attribute of records, we first map values to a multidimensional Euclidean space that preserves domain-specific similarity. Many mapping algorithms can be applied, and we use the Fastmap approach [16] as an example. Given the merging rule that defines when two records are similar based on their attribute-level similarities, a set of attributes are chosen along which the merge will proceed. A multidimensional similarity join over the chosen attributes is used to find similar pairs of records. Our extensive experiments using real data sets show that our solution has very good efficiency and recall.
1386080
Using Constraints to Describe Source Contents in Data Integration Systems
In data integration systems, information sources often have constraints, such as "all houses stored at a source have a unique address." These constraints are useful in computing answers to queries and facilitating information exchange.
10902397
Protecting Individual Information Against Inference Attacks in Data Publishing
In many data-publishing applications, the data owner needs to protect sensitive information pertaining to individuals. Meanwhile, certain information is required to be published. The sensitive information could be considered as leaked, if an adversary can infer the real value of a sensitive entry with a high confidence. In this paper we study how to protect sensitive data when an adversary can do inference attacks using association rules derived from the data. We formulate the inference attack model, and develop complexity results on computing a safe partial table. We classify the general problem into subcases based on the requirements of publishing information, and propose the corresponding algorithms for finding a safe partial table to publish. We have conducted an empirical study to evaluate these algorithms on real data.
2113121
Computing capabilities of mediators
Existing data-integration systems based on the mediation architecture employ a variety of mechanisms to describe the query-processing capabilities of sources. However, these systems do not compute the capabilities of the mediators based on the capabilities of the sources they integrate. In this paper, we proposed a framework to capture a rich variety of query-processing capabilities of data sources and mediators. We present algorithms to compute the set of supported queries of a mediator, based on the capability limitations of its sources. Our algorithms take into consideration a variety of query-processing techniques employed by mediators to enhance the set of supported queries.
3731147
A Multi-tiered Model for Performance Analysis of Storage Area Network
37859404
Single-machine scheduling to minimize the weighted number of early and tardy agreeable jobs
Abstract We consider a single-machine scheduling problem in which every job has a given target start time and a due-date. A job is early if processing commences before its start time and is tardy if it is completed after its due-date. The objective is to minimize the weighted number of early and tardy jobs, with the restriction that the start times and due-dates are “agreeable”, i.e., the start times must increase in the same sequence as the due-dates. We show that the problem is NP-complete in the strong sense. The complexity issues and algorithms for some special cases of this problem are discussed, and heuristic algorithms are developed for the general problem. Computational experiments are conducted to show the effectiveness of the heuristics.
516020
Efficient Processing of Ordered XML Twig Pattern
Finding all the occurrences of a twig pattern in an XML database is a core operation for efficient evaluation of XML queries. Holistic twig join algorithm has showed its superiority over binary decompose based approach due to efficient reducing intermediate results. The existing holistic join algorithms, however, cannot deal with ordered twig queries. A straightforward approach that first matches the unordered twig queries and then prunes away the undesired answers is obviously not optimal in most cases. In this paper, we study a novel holistic-processing algorithm, called OrderedTJ, for ordered twig queries. We show that OrderedTJ can identify a large query class to guarantee the I/O optimality. Finally, our experiments show the effectiveness, scalability and efficiency of our proposed algorithm.
3813961
Using MMQ Model for Performance Simulation of Storage Area Network
The infrastructures of SANs are complex, and the implementations/designs of SANs are varied. So finding a proper modeling method to analysis and simulate SAN performance in a systemic/consistent way is very important for the work efficiency of SAN designers and performance tuners. This paper proposes a methodology of using a multi-tier multiserver queue (MMQ) network system to model a SAN system, which can be generalized to different SAN instances neatly, and be used for both performance analysis and simulation. Besides the main idea and high-level MMQ model, the application of this method is illustrated by constructing a software simulator, which is also designed and implemented in a systemic and reusable style. The simulation validation shows that maximum error range is less than 10%. So we can consider this method a sound solution for the quick performance design comparison and analysis of SAN.
14648575
dChipSNP: significance curve and clustering of SNP-array-based loss-of-heterozygosity data
MOTIVATION
Oligonucleotide microarrays allow genotyping of thousands of single-nucleotide polymorphisms (SNPs) in parallel. Recently, this technology has been applied to loss-of-heterozygosity (LOH) analysis of paired normal and tumor samples. However, methods and software for analyzing such data are not fully developed.


RESULT
Here, we report automated methods for pooling SNP array replicates to make LOH calls, visualizing SNP and LOH data along chromosomes in the context of genes and cytobands, making statistical inference to identify shared LOH regions, clustering samples based on LOH profiles and correlating the clustering results to clinical variables. Application of these methods to prostate and breast cancer datasets generates biologically important results.


AVAILABILITY
The software module dChipSNP implementing these methods is available at http://biosun1.harvard.edu/complab/dchip/snp/


SUPPLEMENTARY INFORMATION
The breast cancer data are provided by Andrea L. Richardson, Zhigang C. Wang and James D. Iglehart.