Dynamic Clustering in Object-Oriented Databases: An Advocacy for Simplicity

International audienceWe present in this paper three dynamic clustering techniques for Object-Oriented Databases (OODBs). The first two, Dynamic, Statistical & Tunable Clustering (DSTC) and StatClust, exploit both comprehensive usage statistics and the inter-object reference graph. They are quite elaborate. However, they are also complex to implement and induce a high overhead. The third clustering technique, called Detection & Reclustering of Objects (DRO), is based on the same principles, but is much simpler to implement. These three clustering algorithm have been implemented in the Texas persistent object store and compared in terms of clustering efficiency (i.e., overall performance increase) and overhead using the Object Clustering Benchmark (OCB). The results obtained showed that DRO induced a lighter overhead while still achieving better overall performance

Three Denerations of DBMS

This paper describes the evolution of data base technology from early computing to the sophisticated systems of today. It presents an overview of the most popular data base management systems architectures such as hierarchical, network, relational and object-oriented. The last section of this paper presents a view of the factors that will influence the future of data base technology

Function-based indexing for object-oriented databases

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1994.Includes bibliographical references (p. 167-171).by Deborah Jing-Hwa Hwang.Ph.D

BlendDB : blending table layouts to support efficient browsing of relational databases

Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2008.Includes bibliographical references (p. 63-65).The physical implementation of most relational databases follows their logical description, where each relation is stored in its own file or collection of files on disk. Such an implementation is good for queries that filter or aggregate large portions of a single table, and provides reasonable performance for queries that join many records from one table to another. It is much less ideal, however, for join queries that follow paths from a small number of tuples in one table to small collections of tuples in other tables to accumulate facts about a related collection of objects (e.g., co-authors of a particular author in a publications database), since answering such queries involves one or more random I/Os per table involved in the path. If the primary workload of a database consists of many such path queries, as is likely to be the case when supporting browsing-oriented applications, performance will be quite poor. This thesis focuses on optimizing the performance of these kinds of path queries in a system called BlendDB, a relational database that supports on-disk co-location of tuples from different relations. To make BlendDB efficient, the thesis will propose a clustering algorithm that, given knowledge of the database workload, co-locates the tuples of multiple relations if they join along common paths. To support the claim of improved performance, the thesis will include experiments in which BlendDB provides better performance than traditional relational databases on queries against the IMDB movie dataset. Additionally, this thesis will show that BlendDB provides commensurate performance to materialized views while using less disk space, and can achieve better performance than materialized views in exchange for more disk space when users navigate between related items in the database.by Adam Marcus.S.M

Information resources management, 1984-1989: A bibliography with indexes

This bibliography contains 768 annotated references to reports and journal articles entered into the NASA scientific and technical information database 1984 to 1989

Grifon: a graphical interface to an object oriented database

The aim of the research outlined in this thesis is to establish what type of interface would be most suitable for object oriented databases. In particular it examines how graphical interface technologies might be used to present the database in a clearer form. In support of the research, a prototype interface system has also been developed to a commercial database to illustrate the practicality of the development of such an interface, and the increased effectiveness of the resultant system. The thesis outlines the features provided by the interface, the benefits accrued from such a system, and the problems associated with its development. Finally, it examines how such a system fits into the current work being carried out in the area of user interaction with databases

Univers: The construction of an internet-wide descriptive naming system

Descriptive naming systems allow clients to identify a set of objects by description. Described here is the construction of a descriptive naming system, called Univers, based on a model in which clients provide both an object description and some meta-information. The meta-information describes beliefs about the query and the naming system. Specifically, it is an ordering on a set of perfect world approximations, and it describes the preferred methods for accommodating imperfect information. The description is then resolved in a way that respects the preferred approximations

An Update Algorithm for Restricted Random Walk Clusters

This book presents the dynamic extension of the Restricted Random Walk Cluster Algorithm by Schöll and Schöll-Paschinger. The dynamic variant allows to quickly integrate changes in the underlying object set or the similarity matrix into the clusters; the results are indistinguishable from the renewed execution of the original algorithm on the updated data set

Client cache management in a distributed object database

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1995.Includes bibliographical references (leaves 137-143).by Mark Stuart Day.Ph.D

A multi-agent crop production decision support system for technology transfer

The purpose of this research was to study agricultural crop production 'decision support systems' as a means of transferring agricultural technology from research labs and plots to producers, extension specialists, agriculture service agencies, and scientists, on the Western Canadian Prairies. A 'decision support system' is a computer program that analyses problems spanning several knowledge or problem areas producing results that aid the management decision-making process. The primary objective was to develop a computer application program that would fulfill the farm manager's decision support needs and be "open" to future enhancements. This interdisciplinary study has a strong agricultural presence in the application context of the resultant computerized agricultural decision support system, with agronomics being the foundation on which the system was built, and computer science being the toolbox used to build it. Farm Smart 2000 is the resultant decision support system, providing "single-window" access to three different tiers of decision support utilizing the Internet, ' expert systems' and integrated multiple heterogeneous 'reusable agents' in a cooperative problem-solving environment. An ' expert system' is a computer program that solves complicated problems, within a specific knowledge or problem area, that would otherwise require human expertise. Expert systems integrated with each other within a decision support system are called 'agents. Reusable agents' are modular computer programs (e.g. expert systems) which can be used in more than one computer application with little or no modification. Farm Smart 2000 provides support for most management aspects of crop production including variety selection, crop rotations, weed management, disease management, residue management, harvesting, soil conservation, and economics, for the crops of wheat, canola, barley, peas, and flax. Tier-3, the most sophisticated level of Farm Smart 2000, is the focus of this dissertation and utilizes multiple reusable agents, integrating them such that they cooperate together to solve complex interrelated crop production problems. A Global Control Expert achieves the required communication and coordination among the agents resulting in an "open system", enabling Farm Smart 2000 to extend its problem-solving capabilities by integrating additional agents and knowledge, without system re-engineering, thereby remaining an ongoing technology transfer vehicle