September 1973 - Vol. 16 No. 9

Methods are presented for computing the equilibrium distribution of customers in closed queueing networks with exponential servers. Expressions for various marginal distributions are also derived. The computational algorithms are based on two-dimensional iterative techniques which are highly efficient and quite simple to implement. Implementation considerations such as storage allocation strategies and order of evaluation are examined in some detail.

Using ideas from information theory, this paper develops a heuristic algorithm that converts a limited entry decision table to a tree structured computer program with near minimum average processing time. The method is applicable to any limited entry decision table and does not require that actions have single rules or that the cost of testing conditions be equal. It is thus more general than the previously published heuristic algorithms. Compared to the optimal algorithm of Reinwald and Soland, this algorithm is easy to code and takes a much smaller translation time; it is thus felt that it is more useful in practice. The algorithm is well suited for manual conversion of decision tables to flowcharts.

This work first discusses the factors that affect file (data base) organization performance, an elusive subject, and then presents a methodology, a model and a programmed system to estimate primarily total storage costs and average access time of several file organizations, given a specific data base, query characterization and device-related specifications. Based on these estimates, an appropriate file structure may be selected for the specific situation. The system is a convenient tool to study file structures and to facilitate as much as possible the process of data base structure design and evaluation.

A standard information retrieval operation is to determine which records in a data collection satisfy a given query expressed in terms of data values. The process of locating the desired responses can be represented by a tree search model. This paper poses an optimization problem in the design of such trees to serve a well-specified application. The problem is academic in the sense that ordinarily the optimal tree cannot be implemented by means of practical techniques. On the other hand, it is potentially useful for the comparison it affords between observed performance and that of an intuitively attractive ideal search procedure. As a practical application of such a model this paper considers the design of a novel tree search scheme based on a bit vector representation of data and shows that essentially the same algorithm can be used to design either an ideal search tree or a bit-vector tree. An experimental study of a small formatted file illustrates the concepts.