Toby J. Teorey

A comparative analysis of disk scheduling policies

Five well-known scheduling policies for movable head disks are compared using the performance criteria of expected seek time (system oriented) and expected waiting time (individual I/O request oriented). Both analytical and simulation results are obtained. The variance of waiting time is introduced as another meaningful measure of performance, showing possible discrimination against individual requests. Then the choice of a utility function to measure total performance including system oriented and individual request oriented measures is described. Such a function allows one to differentiate among the scheduling policies over a wide range of input loading conditions. The selection and implementation of a maximum performance two-policy algorithm are discussed.

Cost/benefit analysis for incorporating human factors in the software lifecycle

New software engineering techniques and the necessity to improve the user interface in increasingly interactive software environments have led to a change in traditional software development methods. Methodologies for improvement of the interface design, an overview of the human factors element, and cost/benefit aspects are explored.

ER model clustering as an aid for user communication and documentation in database design

Entity-relationship clustering promotes the simplicity that is vital for fast end-user comprehension, as well as the complexity at a more detailed level to satisfy the database designers need for extended semantic expression in the conceptual model.

Achieving scalability in OLAP materialized view selection

The goal of on-line analytical processing (OLAP) is to quickly answer queries from large amounts of data residing in a data warehouse. Materialized view selection is an optimization problem encountered in OLAP systems. Published work on the problem of materialized view selection presents solutions scalable in the number of possible views. However, the number of possible views is exponential relative to the number of database dimensions. A truly scalable solution must be polynomial time relative to the number of dimensions. We present such a solution, our Polynomial Greedy Algorithm. Complexity analysis proves scalability, and a performance study verifies the result. Empirical evidence demonstrates benefits close to existing algorithms. We conclude the Polynomial Greedy Algorithm functions effectively where existing algorithms fail dramatically.

NetMod: a design tool for large-scale heterogeneous campus networks

A network modeling tool, called NetMod, which uses simple analytical models to provide the designers of large interconnected local area networks with an in-depth analysis of the potential performance of these systems is presented. This tool can be used in either a university, industrial, or governmental campus networking environment consisting of thousands of computer sites. NetMod is implemented with a combination of the easy-to-use Macintosh software packages, HyperCard, and Excel. The objectives of NetMod, the analytical models, and the user interface are described in detail, along with its application to an actual campus-wide network. >

Incorporating behavioral techniques into the systems development life cycle

The gathering of a variety of human-oriented information is vital in the development stages of a software system. This information can be applied at a given stage to improve the human-computer interface of the software product. To reflect this, new categories of design and/or development effort need to be added tot he traditional systems development stages. These efforts, termed user factor stages, differ from the traditional feasibility studies, requirements analyses, and tests that are currently conducted. The stages offer a flexible series of techniques, which can be compared and contrasted in terms of their expected information benefit, cost, and reliability of data obtained. As a concrete example, the development of a forms interface to a relational database management system illustrates these techniques.

A progressive view materialization algorithm

A data warehouse stores materialized views of aggregate data derived from a fact table in order to minimize the query response time. One of the most important decisions in designing the data warehouse is the selection of materialized views. This paper presents an algorithm which provides appropriate views to be materialized while the goal is to minimize the query response time and maintenance cost. We use a data cube lattice, frequency of queries and updates on views, and view size to select views to be materialized using greedy algorithms. In spite of the simplicity, our algorithm selects views which give us better performance than views that selected by existing algorithms.

The Unified Modeling Language (UML)

This chapter is an overview of the syntax and semantics of the UML class and activity diagram constructs. The Unified Modeling Language (UML) is a graphical language for communicating design specifications for software. The object-oriented software development community created UML to meet the special needs of describing object-oriented software design. UML has grown into a standard for the design of digital systems in general. There are a number of different types of UML diagrams serving various purposes. The class and activity diagram types are particularly useful for discussing database design issues. UML class diagrams capture the structural aspects found in database schemas. UML activity diagrams facilitate discussion on the dynamic processes involved in database design. UML class diagrams and entity-relationship (ER) models are similar in both form and semantics. The original creators of UML point out the influence of ER models on the origins of class diagrams. The influence of UML has in turn affected the database community. Class diagrams appear frequently in the database literature to describe database schemas. A class is a descriptor for a set of objects that share some attributes and/ or operations.

Reference architecture for distributed systems management

Management of computing systems is needed to ensure efficient use of resources and provide reliable and timely service to users. Distributed systems are much more difficult to manage because of their size and complexity, and they require a new approach. A reference architecture for distributed systems management is proposed that integrates system monitoring, information management, and system modeling techniques. Three classes of system management—network services and devices, operating system services and resources, and user applications—are defined within this framework, and a detailed hospital application is presented to clarify the requirements for managing applications. It is argued that the performance management of distributed applications must be considered from all three perspectives. Several management prototypes under study within the COnsortium for Research on Distributed Systems (CORDS) are described to illustrate how such an architecture could be realized.

A Pareto model for OLAP view size estimation

On-Line Analytical Processing (OLAP) aims at gaining useful information quickly from large amounts of data residing in a data warehouse. To improve the quickness of response to queries, pre-aggregation is a useful strategy. However, it is usually impossible to pre-aggregate along all combinations of the dimensions. The multi-dimensional aspects of the data lead to combinatorial explosion in the number and potential storage size of the aggregates. We must selectively pre-aggregate. Cost/benefit analysis involves estimating the storage requirements of the aggregates in question. We present an original algorithm for estimating the number of rows in an aggregate based on the Pareto distribution model. We test the Pareto Model Algorithm empirically against four published algorithms, and conclude the Pareto Model Algorithm is consistently the best of these algorithms for estimating view size.