Performance measurement and analysis of large filestores

PhD ThesisPerformance measurements of two large time-sharing computer systems are presented, with emphasis on their disk filestores. Similarities of process behaviour are found in the measured systems and another system reported in the literature. Individual processes make i/o requests in sequences, or bursts. Burst lengths have a mean of two with a large variance; within a burst, file i/o requests are spatially sequential in intent and are temporally related. Characterizations of these behaviour patterns form the basis of a methodology for filestore evaluation and design. Descriptions of spatial and temporal load are abstracted from software traces without loss of any performance factor; these descriptions are inputs to a statistical model of the processes in the environment of the filestore. The filestore is represented by a simulation queuing model. The method specifies the inputs to the composite model and describes the calibration of outputs to match observable outputs. A model is built by this method, and validated for different loads. The model is used for three evaluation experiments. Disk request scheduling is not statistically significant; filestore layout and disk capacity are highly significant; disks with fast-access areas are shown to improve performance by taking advantage of spatial accessing patterns. The limits of performance of a novel filestore equipped with a cache store are explored to determine guidelines for this new design. Modest improvements resulting from this design are shown to produce a considerable improvement in overall system performance.The Science Research Council: The University of Newcastle upon Tyne

A modelling approach to the evalution of computer system performance

Imperial Users onl

Advanced data management system analysis techniques study

The state of the art of system analysis is reviewed, emphasizing data management. Analytic, hardware, and software techniques are described

System Concepts and Formal Modelling Methods for Business Processes

The major quality breakthrough of the 1980s was the realisation by management that business and manufacturing processes are the key to customer service and organisational performance. This thesis is concerned with the overall problem of modelling of business processes. Of special interest is the study of business processes through an interdisciplinary approach that cuts across the boundaries of management and information technology. The overall effort is placed on being able to move from a purely conceptual level of describing a business process to a more formal one, enabling decision making, and driving the analysis away from experience, intuition, and informal debate. The extended review and presentation of the various modelling methodologies given here, serve as a guide to their basic concepts and capabilities. A particular case study - the management of the human resources in a consulting company - has been used in this thesis to enable the evaluation of the modelling techniques. Hence, models have been produced, as well as simulation results to indicate the limitations, the advantages and the information gained. Through this application, the understanding of requirements for modelling analysis and decision making of business processes was acquired. Particularly, two very important techniques were investigated. System Dynamics and Petri nets provide the answers when process models are geared to deliver not only qualitative but also quantitative results. However, Petri nets provide the mathematical notation and the plethora of analysis tools needed for the validation, verification, and performance analysis of the model. Additionally, two different simulation software packages were used, based on these methodologies; Ithink®, which is based on System Dynamics, and Alpha/Sim®, based on Petri nets theory. The model produced in the case study depicts perfectly the capabilities of the two techniques. Petri nets is not the total business modelling solution, it can be complemented by other methods, such as System Dynamics and discrete-time modelling as shown in Chapter 6. The feasibility of all these modelling techniques lies entirely on the analyst, who should use them alternately to satisfy the requirements of the problem