Ross A. Gagliano

Granular neural networks for numerical-linguistic data fusion and knowledge discovery

In this paper, we present a neural-networks-based knowledge discovery and data mining (KDDM) methodology based on granular computing, neural computing, fuzzy computing, linguistic computing, and pattern recognition. The major issues include 1) how to make neural networks process both numerical and linguistic data in a data base, 2) how to convert fuzzy linguistic data into related numerical features, 3) how to use neural networks to do numerical-linguistic data fusion, 4) how to use neural networks to discover granular knowledge from numerical-linguistic data bases, and 5) how to use discovered granular knowledge to predict missing data. In order to answer the above concerns, a granular neural network (GNN) is designed to deal with numerical-linguistic data fusion and granular knowledge discovery in numerical-linguistic databases. From a data granulation point of view, the GNN can process granular data in a database. From a data fusion point of view, the GNN makes decisions based on different kinds of granular data. From a KDDM point of view, the GNN is able to learn internal granular relations between numerical-linguistic inputs and outputs, and predict new relations in a database. The GNN is also capable of greatly compressing low-level granular data to high-level granular knowledge with some compression error and a data compression rate. To do KDDM in huge data bases, parallel GNN and distributed GNN will be investigated in the future.

Auction allocation of computing resources

Standard methods for allocating computing resources normally employ schedulers and either queue or priority schemes. Alternative methods utilizing marketlike processes are being investigated, with direct applicability to evolving distributed systems. In this article, we present results of simulations of an auction allocation is which computing tasks are provided sufficient intelligence to acquire resources by offering, bidding, and exchanging them for funds.

Modeling The Cost Of Resource Allocation In Distributed Control

Modifying our previously developed simulation model [FRA89], we study in this paper the costs associated with distributed allocation of computing resources in a multitasking environment. Using funds endowed upon arrival, computing tasks compete for necessary resources through sealed-bid auctions to improve their processing schedules. The costs and times dedicated to auctioning are compared to the costs and times allowed for task processing. Measuring computing resources in terms of processing rates allows the task management, in the form of an auction, algorithm, to have its requirements specified in the same way as the requirements for the simulated mission processing. Machine capacity is computed for and assigned to each completing task. Data are then compiled by segmented capacity classes. A unifying theme of past and current research is the efficiency of auctioning to allocate reconfigurable computing resources in a variable capacity machine. We observed that at optimal rates of occurrence of capacity classes which minimize the total costs per successful completion, congestion was resolved through auctions generating endogenously implied prices which substantially exceeded the exogenously imposed price.

The simulation of a distributed control model for resource allocation and the implied pricing

The allocation of computing resources and the scheduling of tasks in a multitasking environment are simulated using a distributed control model. The tasks compete for computing resources in a decentralized manner through sealed bid auctions to improve their schedules, rather than having resources centrally administered by a host controller. Funds used for bidding are endowed to the tasks upon arrival at the computing system. The effects on completion times of three endowment strategies and two machine sizes are analyzed using a range of system capacities. Within each capacity class, an apparent cost, derived from the run parameters, is contrasted with an implied price generated by the auction process. Performance is examined in terms of congestion at various capacities. At optimal (lowest cost per successful completion) rates of occurrence of these capacity classes, an implied price arises that exceeds the “free access” price. This internally generated price appears to ration resources and time, thus discouraging congestion. Implementing such a distributed control algorithm suggests that determining a price schedule for allocating computing resources can be moved “to the left” in the system life cycle.

The simulation of decentralized control: a hostless resource allocation model

In this article, an alternative approach to control for computing systems, with possible distributed, parallel, or multilprocess application, is proposed and evaluated through simulation. Functions normally handled by centralized controllers, schedulers, arbiters and priority schemes are accomplished through a decentral ized model of control. Resource allocation, one important control function, is resolved within a Challenge Ring (CR) in which individual computing tasks independently (or without a host, hence their interaction is called hostless) exercise algorithms to gain access to computing resources. Simulated system performance is monitored by analyzing individual task processing times, total system times, resource availability, resource utilization, and system efficiency. Our preliminary experimental results indicate that such decentralized (or hostless) models can be superior to some standard centralized (or hosted) versions. Moreover, tasks in CR networks that interact through cooperative strategies in some cases exhibit better performance. Our overall results encourage the further exploration of decentralized control models which could be useful in the continuing pursuit of alternative machine constructs (e.g. non-von Neumann architectures) and new distributed operational schemes (e.g. hostless network operating systems).

Issues in Reusable ADA Library Tools

This current research program on software reuse is investigating library tools fordescribing,classifying,cataloging, organizing and managing Ada reusable software components. The major research results are the development and prototyping of classification methods and the evaluation of library tools for software reuse generally, and Ada components for management information systems specifically. The prototype system integrates the Faceted Classification Scheme (FCS) and conceptual closeness maps. Future research areas include the development of tools for reusable components libraries and expert systems for software development with natural language interfaces.

Software agents and the role of market protocols

A crucial need exists for innovative means to access, secure, and maintain distributed or networked resources such as those found on the Internet. Instead of centralized controllers, schedulers, and priority schemes, we advocate the use of decentralized approaches such as software agents with autonomous protocols. We have proposed protocols for agents which represent tasks that negotiate to gain access to computing resources such as Web files, graphics processors, databases, special output devices, etc. Four different market protocols have been developed (single action, auction, barter, and challenge), and through simulation, associated system performance has been analyzed by monitoring agent and task performance; viz, processing times, total system times, resource availability, resource utilization, and system efficiency. Experimental results show that agents using market protocols are more effective than the standard hosted approaches, encouraging their possible further exploration into non-von Neumann architectures and hostless network operating systems.

Annotated bibliography of the proceedings of the annual simulation symposium (1968-1991)

An annotated bibliography is being developed for the 435 papers that have been published in the Proceedings of the Annual Simulation Symposium since 1968. Using the Paradox relational database system, this catalog of the 24 volumes of papers contains descriptions and data of topical and indexical value. These papers track the evolution of the simulation discipline through changes in its subject matter; e.g., issues of simulation techniques, technology, languages, and applications, etc. This article presents a very brief analysis of some of the more notable trends and an appendix listing the titles of the papers alphabetized by author with an index of the symposium number followed by paper number.<<ETX>>

Knowledge Based Tools for Reusable ADA Software

Based on a research program at Georgia State University on software reusability and metrics, an investigation is being made into library tools for managing Ada Reusable Software Components (RSC’s). The effort is directed towards the development and evaluation of library tools that will be useful in managing libraries of Ada RSC’s. A major focus of the work, and the primary subject for this paper, is the development of a Knowledge Based Software Assistant (KBSA) to ease the transition from informal to formal requirements and specifications. This system will interact with the user in a domain specific limited natural language to generate a set of formal specifications or requirements in one of the currently used formalisms. We plan to interface this system with our RSC storage and retrieval system, which was presented in the companion paper.

Software Pattern Constructs

A software pattern construct is a syntactical structure in a higher order language which provides examples of correct format for common programming expressions. Typical applications include: input and output phrasing and the use of prompts; control structures; conditional and logical constructs; and secondary data structures as arrays, records, and files. This paper attempts to describe software patterns, and to provide motivation and examples for their use with several languages in an evolving on-line reference system.