Encoded bitmap indexing for data warehouses
Complex query types, huge data volumes, and very high read/update ratios make the indexing techniques designed and tuned for traditional database systems unsuitable for data warehouses (DW). We propose an encoded bitmap indexing for DWs which improves the performance of known bitmap indexing in the case of large cardinality domains. A performance analysis and theorems which identify properties of good encodings for better performance are presented. We compare encoded bitmap indexing with related techniques, such as bit slicing, projection-, dynamic-, and range-based indexing.

title: Research Issues in Data Warehousing
abstract: Data warehousing is a booming industry with many interesting research problems. The database research community has concentrated on only a few aspects. In this paper, We summarize the state of the art, suggest architectural extensions and identify research problems in the areas of warehouse modeling and design, data cleansing and loading, data refreshing and purging, metadata management, extensions to relational operators, alternative implementations of traditional relational operators, special index structures and query optimization with aggregates.

title: Supporting Group-By and Pipelining in Bitmap-Enabled Query Processors
abstract: The Group-By operation is widely used in relational Data Warehouses for the aggregation and presentation of results according to user-defined criteria. Rearranging Group-By and join operations has been proposed as an optimization technique that reduces the size of the input relation. Pipelining is another optimization technique that promotes intra-query parallelism by transfering intermediate results to the next operation without materializing them. In Data Warehouses and environments in which exploratory on-line queries are common, pipelining can be used both for optimizing joins and for the reduction of response time by presenting partial results to the user. Efficient pipelining often depends on the order of the intermediate results. Order-dependent operations, such as Group-By, typically require the complete result set before ordering it, thereby making efficient pipelining impossible. In this paper we exploit bitmap indexing to implement Group-By in a manner that can be used for pipelining. Algorithms are presented for different assumptions about buffer availability and for different sort orders.

title: A Hyperrelational Approach to Integration and Manipulation of Data in Multidatabase Systems
abstract: The issue of interoperability among multiple autonomous databases has attracted a lot of attention from researchers in these years. The past research on this issue can be roughly divided into two main categories: the tightly-integrated approach that integrate databases by building an integrated schema and the loosely-integrated approach that achieves interoperability by using a multidatabase language. Most of the past efforts focused on the issues in the first approach. The problem with the first approach is, however, that it lacks a convenient representation of the integrated schema at the system level and a sound mathematical basis for data manipulation in a multidatabase system. In this paper, we propose to use hyperrelations as a powerful and succinct model for the global level representation of heterogeneous database schemas. A hyperrelation has the structure of a relation, but its contents are the schemas of the semantically equivalent local relations in the databases. With this representation, the metadata of the global database, local databases and the data of these databases are all representable by using the structure of a relation. The impact of such a representation is that all the elegant features of relational systems can be easily extended to multidatabase systems. A hyperrelational algebra is designed accordingly. This algebra is performed at the multidatabase systems (MDBS) level such that query transformation and optimization is supported on a sound mathematical basis. The major contributions of this paper include: (1) Local relations of various schemas (even though they retain information of the same semantics) can be systematically mapped to hyperrelations. As the structure of a hyperrelation is similar to that of a relation, data manipulation and management tasks (such as design of the global query language and the view mechanism) are greatly facilitated. (2) The hyperrelational algebra provides a sound basis for query transformation and optimization in a MDBS.

title: Query optimization for selections using bitmaps
abstract: Bitmaps are popular indexes for data warehouse (DW) applications and most database management systems offer them today. This paper proposes query optimization strategies for selections using bitmaps. Both continuous and discrete selection criteria are considered. Query optimization strategies are categorized into static and dynamic. Static optimization strategies discussed are the optimal design of bitmaps, and algorithms based on tree and logical reduction. The dynamic optimization discussed is the approach of inclusion and exclusion for both bit-sliced indexes and encoded bitmap indexes.

title: Digital watermarking using shuffling
abstract: This paper applies shuffling to digital watermarking and data hiding. The data embedding capacity in the multimedia source generally varies significantly from one part of the source to another. Sequential embedding is very sensitive to noise which may cause synchronization problem; the common but conservative solution via partitioning an image into large segments and embedding only one bit per segment is wasteful of the data embedding capacity. This paper shows how random shuffling can be used to equalize the uneven distribution of embedding capacity. The effectiveness of random shuffling is demonstrated by analysis and experiments.

title: Myriad: An Architecture for Contextualized Information Retrieval and Delivery
abstract: Users’ information needs are largely driven by the context in which they make their decisions. This context is dynamic. It includes the users’ characteristics, their current domain of application, the tasks they commonly perform and the device they are currently using. This context is also evolving. When one information need is satisfied, another is likely to emerge. An information access system must, therefore, be able to track this dynamic and evolving context, and exploit it to retrieve actionable information from appropriate sources and deliver it in a form suitable for the current situation. This paper presents a generic architecture that supports the construction of information retrieval and delivery systems that make use of context. The architecture, called Myriad, includes an adaptive virtual document planner, and explicit, dynamic representations of the user’s current context.

title: Picard--Vessiot extensions for linear functional systems
abstract: Picard-Vessiot extensions for ordinary differential and difference equations are well known and are at the core of the associated Galois theories. In this paper, we construct fundamental matrices and Picard-Vessiot extensions for systems of linear partial functional equations having finite linear dimension. We then use those extensions to show that all the solutions of a factor of such a system can be completed to solutions of the original system.

title: Data Hiding in Compiled Program Binaries for Enhancing Computer System Performance
abstract: Information hiding has been studied in many security applications such as authentication, copyright management and digital forensics. In this work, we introduce a new application where successful information hiding in compiled program binaries could bring system-wide performance improvements. Our goal is to enhance computer system performance by providing additional information to the processor, without changing the instruction set architecture. We first analyze the statistics of typical programs to demonstrate the feasibility of hiding data in them. We then propose several techniques to hide a large amount of data in the operand fields with very low computation and storage requirements during the extraction process. The data embedding is made reversible to recover the original instructions and to ensure the correct execution of the computer program. Our experiments on the SPEC CPU2000 benchmark programs show that up to 110K bits of information can be embedded in large programs with as little as 3K bits of additional run-time memory in the form of a simple look-up table.

title: Classification-based spatial error concealment for images
abstract: This paper presents a new, classification-based spatial error concealment algorithm for images. The proposed scheme takes advantage of two state-of-the-art concealment schemes and adaptively selects a better suitable concealment scheme for each corrupted block. Using a support vector machine (SVM) classifier, our proposed approach outperforms the prior art in terms of the concealment quality and has moderate computational complexity.