Computer Capacity Planning Research Articles

Optimal Resource Capacity Management for Stochastic Networks

We develop a framework for determining the optimal resource capacity of each station composing a stochastic network, motivated by applications arising in computer capacity planning and business process management. The problem is mathematically intractable in general and therefore one typically resorts to either simplistic analytical approximations or time-consuming simulation-based optimization methods. Our solution framework includes an iterative methodology that relies only on the capability of observing the queue lengths at all network stations for a given resource capacity allocation. We theoretically investigate this proposed methodology for single-class Brownian tree networks and illustrate the use of our framework and the quality of its results through computational experiments.

Computer Capacity Planning Management: Definitions and Methodology

Information systems (IS) managers are asked to provide services and cut computer costs. Computer capacity planning (CCP) provides them with a tool to assess the future computing needs and new technologies. Effective CCP is an important step in providing users with the lowest cost solution that meets their computing requirements. This paper discusses the definition and methodologies of CCP. The importance of CCP for IS people as well as business people is emphasized. Five phases for developing a capacity plan are presented and a few examples for illustration are provided. A real life example is also presented and suggestions and recommendations are offered.

Computer capacity planning management: definitions and methodology

Information systems (IS) managers are asked to provide services and cut computer costs. Computer capacity planning (CCP) provides them with a tool to assess the future computing needs and new technologies. Effective CCP is an important step in providing users with the lowest cost solution that meets their computing requirements. This paper discusses the definition and methodologies of CCP. The importance of CCP for IS people as well as business people is emphasized. Five phases for developing a capacity plan are presented and a few examples for illustration are provided. A real life example is also presented and suggestions and recommendations are offered.

Understanding laboratory information management system software performance in a pharmaceutical development environment

In today's competitive business environments it has become increasingly important to select computer systems which are suitable, efficient, flexible and cost effective. Computer performance analysis and capacity planning can be used as tools to assist in meeting these business needs. The analysis described was undertaken to provide, through an understanding of the capabilities and limitations of a system running laboratory information management system (LIMS) application software, an accurate purchase recommendation for our production LIMS. This understanding, in turn, has provided other cost-related benefits, in addition to significant system management benefits.

An empirical study of computer capacity planning in U.S. universities

Computer systems managers need to understand their applications and growth environment to analyze the current and predicted future workload, and plan for future capacity to meet business needs. This paper studies the computer capacity planning (CCP) practices at US universities to provide insight for computer capacity planners and administrators. Data were collected from 170 academic institutions in an attempt to learn the extent to which the various approaches and techniques of CCP are used there and to identify several important environmental factors affecting their use in practice. The study also examined the differences in CCP approaches between US universities and US industries. Results show that the computing environment is more interactive in universities and the computing budget is less than the computing budget of industry, but the basic approaches to CCP in universities are similar to those of in industry.

Decision Support for Supercomputer Acquisition

This paper reports on a decision support system (DSS) for computer capacity planning. The system was developed for Sandia National Laboratories (SNL) to support planning in an environment characterized by large-scale scientific computing needs, governmental budgetary limitations and specific planning documentation required by the funding source. The implementation of the system is based directly on the concepts of relational model management and logic-based model representation and manipulation. The implementation vehicle for this system is an extended version of Prolog, which allows interactions with externally defined computational routines and sources of data. This vehicle provides for the integration of various data sources with a set of models for estimating capacity requirements and optimizing different objective functions subject to budgetary constraints.

Book review: Computer Systems Performance Management and Capacity Planning by J. Cady and B. Howarth (Prentice-Hall, 1990)

I reviewed this book from the author's manuscript. The book is now being typeset, and the author tells me that it is due to appear in February, 1991.

A prolog-based decision support system for computer capacity planning

This paper describes a project to implement a decision support system for computer capacity planning. The system provides an intelligent interface to the various models needed for this type of planning by assisting the user in model formulation, data manipulation, model execution, interpretation and manipulation of results. The implementation strategy is based on the integration of relational model and database management with logic. A modified version of a Prolog interpreter is utilized as the vehicle for this integrated strategy.

An empirical study of computer capacity planning in Japan

Capacity planners in Japan rely heavily on intuitive and judgmental approaches in their computer capacity planning functions, even more so than their U.S. counterparts, according to the following survey. The emphasis in large Japanese firms on job rotations, lifetime employment, and extensive social and informal interaction among employees helps contribute to the effectiveness of these judgmental methods.

Logic-based decision support for computer capacity planning

This paper reports on a decision support system for computer capacity planning. The system is currently under development for Sandia National Laboratories to support planning in an environment characterized by large scale scientific as well as more traditional administrative computing needs, governmental budgetary limitations, and specific planning documentation required by the funding source. The implementation vehicle for this system is an extended version of Prolog which allows interactions with externally defined computational routines and sources of data. This provides for the integration of various data sources with a set of models for estimating capacity requirements and optimizing different objective functions subject to budgetary constraints. This paper outlines the decision environment, pointing out the benefits of using a DSS to support management in forecasting user requirements and optimizing their supercomputer acquisitions, subject to cost, time, financial options and user needs.

Organizational Factors Affecting Capacity Planning Practices

Because of the high cost of most major equipment acquisitions, even a small improvement in the computer capacity planning (CCP— process can result in significant cost savings. The survey results presented here assess the effects of computing organization characteristics on various aspects of CCP practices. The results also should help MIS managers and analysts broaden their understanding of how this function can be conducted and what factors significantly affect its practice.

Computer System Performance Evaluation Using Queueing Network Models

This paper reviews recent developments in the use of practical queueing­ based tools, particularly queueing network models, to study the performance of computer systems. We emphasize those research results that have been responsible for the successful transfer of this technology-the widespread use of these tools in computer system design, sizing, and capacity planning by people whose expertise lies in these application areas, rather than in modeling or mathematics. Queueing theory as a discipline dates from the 1920s. Almost without exception, the results of the early decades concern models of single conges­ tion points. These results encompass a wide variety of specific assumptions about the arrival process, the service process, the scheduling discipline, the queue size limitation, etc. Applications of these single resource models are found in many areas, particularly operations research, management science, and industrial engineering. In computer system engineering, these models have met with great success when used by skilled practitioners for the one-time analysis of subsystems, e.g. a specific communication network

Computer capacity planning

This article defines computer capacity planning and proposes a four-phased model for computer capacity planning (CCP). The model contains the major steps needed for developing a comprehensive computer capacity plan. The requirements for capacity planning are defined in terms of people, hardware, software, and computing resources. Common tools and methodologies for each step in the planning process are described, including a discussion of the advantages and disadvantages of each. This article provides guidelines for the development of a formal capacity planning function.