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Data replication is often used to increase the availability of data in a database system. Voting schemes can be used to manage this replicated data. In this paper we use a simple model to study the capacity of systems using voting schemes for data management. Capacity of a system is defined as the number of operations the system can perform successfully, on an average, per unit time. We study the capacity of a system using voting and compare it with the capacity of a system using a single node. We show that the maximum increase in capacity by the use of majority voting is bounded by lip, where p is the steady-state probability of a node being alive. We also show that for a system employing majority voting, if the reliability of nodes is high, increasing the number of nodes to more than three gives only a marginal increase in capacity. We perform similar analysis for three other voting schemes. [ABSTRACT FROM AUTHOR]

Data access cost evaluation is fundamental in the design and management of database systems. When some data items have duplicates, a clustering effect which can heavily influence access costs is observed. The availability of a finite amount of buffer memory in real systems has an even more dramatic impact. In this paper a comprehensive cost model for clustered data retrieval by an index using a finite buffer is presented. Our approach combines and extends previous models based either on finite buffer or on uniform data clustering assumptions. The computational cost of the formulas we propose in this work is independent of the data size or of the query cardinality and need only a single statistics per search key, the clustering factor, to be maintained by the system. The predictive power and the accuracy of the model are shown in comparison with actual costs resulting from simulations. [ABSTRACT FROM AUTHOR]

Commercially available database systems do not meet the information and processing needs of design and manufacturing environments. A new generation of systems-engineering Information systems-must be built to meet these needs. In this paper, we address the architectural and computational aspects of such systems and propose solutions. We argue that a mainframe-workstation architecture is needed to provide distributed functionality while ensuring high availability and low communication overhead, that explicit control of meta-knowledge is needed to support extendibility and evolution, that large rule bases are needed to make the knowledge of the systems active, and that incremental computation models are needed to achieve the required performance of such engineering information systems. [ABSTRACT FROM AUTHOR]

Data structure diagrams are two-dimensional figures made up of lines that aim to pictorially indicate the interrelationships of the elements of a data structure. This paper collects the various rules and factors of aesthetics that go into the way we draw data structure diagrams. We formulate the various subjective factors into computable objectives and numeric parameters. These are distilled from a large number of data structure drawings as found in various textbooks. We reveal that the rules used have not reached a level of acceptance compared to the relevant rules in engineering graphics. We also outline the internal architecture of a (sub)system that we are building that helps draw data structure diagrams. [ABSTRACT FROM AUTHOR]

Software size estimation has been the object of a lot of research in the software engineering community due to the need of reliable size estimates in the utilization of existing software project cost estimation models. This paper discusses the strengths and weaknesses of existing size estimation techniques, considers the nature of software size estimation, and presents a software size estimation model which has the potential for providing more accurate size estimates than existing methods. The proposed method takes advantage of a characteristic of object-oriented systems, the natural correspondence between specification and implementation, in order to enable users to come up with better size estimates at early stages of the software development cycle. Through a statistical approach the method also provides a confidence interval for the derived size estimates. The relation between the presented software sizing model and project cost estimation has also been considered. [ABSTRACT FROM AUTHOR]

In spite of their advantage in removing the overhead of lock maintenance and deadlock handling, optimistic concurrency control methods have continued to be far less popular in practice than locking schemes. There are two complementary approaches to help render the optimistic approach practically viable. For the high-level approach, integration schemes can be utilized so that the database management system is provided with a variety of synchronization methods each of which can be applied to the appropriate class of transactions. The low-level approach seeks to increase the concurrency of the original optimistic method and improve its performance. In this paper we examine the latter approach, and present algorithms that aim at reducing backups and improve throughput. Both the single-site and distributed networks are considered. Optimistic schemes using time-stamps for fully duplicated and partially duplicated database networks are presented, with emphasis on performance enhancement and on reducing the overall cost of implementation. Abstract-A methodology is presented for evaluating the performance of database update schemes in a distributive environment. The methodology makes use of the history of how data are used in the database. Parameters, such as update to retrieval ratio and average file size, can be set based on the actual characteristics of a system. The analysis is specifically directed toward the support of derived data within the relational model. Because concurrency is a major problem in a distributive system, the support of derived data is analyzed with respect to three distributive concurrency control techniques- master/slave, distributed, and synchronized. [ABSTRACT FROM AUTHOR]

Composite objects are descriptions of assemblies of parts which themselves can be assemblies of other parts. Efficient storage and retrieval of composite objects is essential for computer aided design applications of database management systems. This paper introduces a clustering concept called component aggregation which considers assemblies having the same types of parts as equivalent objects. The notion of equivalent objects is used to develop a mathematical model of composite objects. It is shown that the set of equivalence classes of objects form a Boolean algebra whose minterms represent the objects which are not considered composite at the current viewing level. The algebraic structure of composite objects serves as a basis for developing a technique for organizing composite objects and supporting materialization of explosion views. The technique provides a clubstering mechanism which partitions the database into meaningful and application-oriented clusters, and allows any desired explosion view to be materialized using a minimal set of stored views. A simplified relational database for design data, and a set of frequent access patterns in design applications are outlined and used to demonstrate the benefits of database organization based on the mathematical model of composite objects. [ABSTRACT FROM AUTHOR]

As the social demand on database utilization expands, database systems are being directly handled more and more by non- professionals. In this field, it is important that friendly user-interfaces are provided. It has been found that nonprocedural ways of describing queries such as QRE are preferred. A further step toward attaining a higher degree of user-friendliness would be the development of a way of enabling the system to perform a flexible interpretation of queries usually specified definitely by the user. A flexible interpretation is necessary so that data items which are semantically close to an exact match with the query conditions can be obtained. This paper presents a relational database system, ARES, which has the capability of performing a flexible interpretation of queries. In ARES, relational operations have been functionally augmented with an additional comparison operator which implies "approximately equal to" or "similar to" for cases in which the user expects the system to perform a flexible interpretation of the query conditions. The functional augmentation is simply achieved by a combination of conventional relational operations. ARES is now in actual operation in a research environment, and will contribute to the next step of our research toward implementation of highly intelligent data processing facilities beyond the present scope of database technology. [ABSTRACT FROM AUTHOR]

Decentralized consensus protocols are characterized by successive rounds of message interchanges. Protocols which achieve a consensus in one round of message interchange require O(N²) messages, where N is the number of participants. In this paper, we present a communication scheme, based on finite projective planes, which requires only O(N√N) messages for each round. Using this communication scheme, we develop decentralized consensus protocols which achieve a consensus within two rounds of message interchange. The protocols are symmetric, and the communication scheme does not impose any hierarchical structure. We illustrate our scheme using blocking and nonblocking commit protocols, decentralized extrema finding, and computation of the sum function. [ABSTRACT FROM AUTHOR]