A new approach to performance modelling of Client/Server distributed data base architectures

The recent technological advances in the field of computer and communication lead to distributed data base (DDB) architectures based on the Client/Server paradigm. Available DDB performance prediction methodologies are not sufficiently adequate being too expensive both in the model definition and in the model analysis because of the structural complexity and the large system dimension.

This paper concentrates on a new approach to performance modeling of DDB systems called “independent modelling approach”. This approach separates the DDB software model from the DDB machinery model, and models from solution techniques. This way the aspects related to data contention can be analysed as a pure software characteristic and separated from resource contention, considered as a machinery characteristic. Furthermore, it is possible to analytically model some system aspects (e.g., the software only, or part of it, without involving the machinery model), and apply combined analytical/simulation methods for the remaining system aspects. This results in higher flexibility at lower computational cost in the performance analysis of complex DDB architectures.

A case study is developed and experimental results are discussed to show the effectiveness of the approach.     

A systematic modelling and simulation approach for JIT performance optimisation

Robust computer aided simulation and modelling tools help to visualise, analyse and optimise complex production processes with a reasonable amount of time and investment. A review of the literature shows that simulation and modelling have not been extensively applied in just-in-time (JIT) manufacturing environments. Also there remains a lack of a comprehensive mechanism to identify the most significant JIT drivers for the purpose of system process optimisation. The prime objective of this study is to close this gap by applying computer based simulation tools and linear mathematical modelling to identify the impact of selected key JIT parameters on performance in an automotive component-manufacturing environment. Research shows that variables such as inconsistent task distribution, variation on operator performance, misconception of total quality management philosophy and lack of set-up time elimination plans disrupt ideal JIT production. In this study, ProModel simulation and modelling software is used to model and simulate different experimental scenarios in order to understand and quantify the impact of selected input key JIT variables on objective functions (i.e. process time and takt time). The outcome is a robust mathematical model that highlights the significance of JIT drivers in the manually operated mixed-model assembly lines.     

Driver performance modelling and its practical application to railway safety

This paper reports on the development and main features of a model of driver information processing. The work was conducted on behalf of Network Rail to meet a requirement to understand and manage the driver's interaction with the infrastructure through lineside reminder appliances. The model utilises cognitive theory and modelling techniques to describe driver performance in relation to infrastructure features and operational conditions. The model is capable of predicting the performance time, workload and error consequences of different operational conditions. The utility of the model is demonstrated through reports of its application to the following studies:

Research on the effect of line speed on driver interaction with signals and signs.

Calculation of minimum reading times for signals.

Development of a human factors signals passed at danger (SPAD) hazard checklist, and a method to resolve conflicts between signal sighting solutions.

Research on the demands imposed on drivers by European train control system (ETCS) driving in a UK context.

The paper also reports on a validation of the model's utility as a tool for assessing cab and infrastructure drivability.     

Compositional performance modelling with the TIPPtool

Stochastic process algebras have been proposed as compositional specification formalisms for performance models. In this paper, we describe a tool which aims at realising all beneficial aspects of compositional performance modelling, the TIPPtool. It incorporates methods for compositional specification as well as solution, based on state-of-the-art techniques, and wrapped in a user-friendly graphical front end. Apart from highlighting the general benefits of the tool, we also discuss some lessons learned during development and application of the TIPPtool. A non-trivial model of a real life communication system serves as a case study to illustrate benefits and limitations.     

Coloured Petri Nets and CPN Tools for modelling and validation of concurrent systems

Coloured Petri Nets (CPNs) is a language for the modelling and validation of systems in which concurrency, communication, and synchronisation play a major role. Coloured Petri Nets is a discrete-event modelling language combining Petri nets with the functional programming language Standard ML. Petri nets provide the foundation of the graphical notation and the basic primitives for modelling concurrency, communication, and synchronisation. Standard ML provides the primitives for the definition of data types, describing data manipulation, and for creating compact and parameterisable models. A CPN model of a system is an executable model representing the states of the system and the events (transitions) that can cause the system to change state. The CPN language makes it possible to organise a model as a set of modules, and it includes a time concept for representing the time taken to execute events in the modelled system. CPN Tools is an industrial-strength computer tool for constructing and analysing CPN models. Using CPN Tools, it is possible to investigate the behaviour of the modelled system using simulation, to verify properties by means of state space methods and model checking, and to conduct simulation-based performance analysis. User interaction with CPN Tools is based on direct manipulation of the graphical representation of the CPN model using interaction techniques, such as tool palettes and marking menus. A license for CPN Tools can be obtained free of charge, also for commercial use.     

Formal modelling of organisational goals based on performance indicators

Every organisation exists or is created for the achievement of one or more goals. To ensure continued success, the organisation should monitor its performance with respect to the formulated goals. In practice the performance of an organisation is often evaluated by estimating its performance indicators. In most existing approaches for organisation modelling the relation between performance indicators and goals remains implicit. This paper proposes a formal framework for modelling goals based on performance indicators and defines mechanisms for establishing goal satisfaction, which enable evaluation of organisational performance. Methodological and analysis issues related to goals are also discussed in the paper. The described framework is a part of a general framework for organisation modelling and analysis.     

An integrated modelling environment for the embodiment of mechanical systems

The efficient, economical and often elegant transformation from a design schema to an embodied design solution containing real components is essential for the commercial success of a product. More often the ability of the designer to explore an optimum solution is severely frustrated by the analytically intensive and time-consuming aspects of embodying a concept. This paper presents a computer based system-modelling tool that is to be used by designers during the transformation of a concept to an embodied solution particularly to deal with standard components. This environment provides for the representation of conceptual schemas and subsequent embodiment from computer based component selection modules. These selection modules encompass the full range of electronic representations for standard mechanical components. The strategy for representing a mechanical system, its included components and their associated representations is discussed. The process of constructing a system model, specifying the desired performance characteristics and system resolution are also described.     

A unified approach to deadbeat systems design

This paper is concerned with the design of a discrete-time regulator by using an observer in conjunction with a state feedback law. Previous techniques have been examined, modified, and simplified to a unified procedure. For example, in the initial step, Krylov's transformation is used which has never been applied explicitly. In the second step, an alternate use of Krylov's transformation is demonstrated to design feedback laws that achieve eigenvalue placement. In the final stage of the controller design, the combination of the observer and the state feedback law is clearly seen. Two new matrix identities are derived and applied in the transfer function manipulation.     

A unified approach to synthesis of linear systems

A simple procedure for direct synthesis of linear feedback systems which is applicable to either continuous or sampled data processes is derived. Given the transfer function of the process to be controlled and constraints on desired closed-loop dynamics, the procedure yields an exact analytical solution for the transfer function of the required compensator without recourse to graphical techniques. Suitable constraints include specification of any or all closed-loop poles and/or specification of the position, velocity, or acceleration error constant. Design for specified rise time, overshoot, mean-squared error, etc., may be accomplished by using an iterative routine. The procedure is ideally suited for implementation by digital computer and has been applied to a simulated adaptive flight control system which required that the entire compensator design procedure be executed by a computer without the aid of human intervention.     

Near-optimal state feedback design for singularly perturbed systems by unified approach

A near optimal state feedback design for singularly perturbed systems by a unified approach using the delta operator is presented with an example of the aircraft longitudinal motion. The main contribution of this paper is to explore the use of the i -operator that has attracted a new attention in systems science. The i -operator system unifies the continuous system and the discrete system together without loosing any characteristics of both systems. The paper offers the following; Finite-word-length-characteristics are improved using the i -operator. Floating-point-operations are reduced by block diagonalization and by time-invariant optimal feedback gain from the algebraic Riccati equation. The results of adopting those approaches are illustrated in the simulation figures and compared with the earlier one.     

A new adaptive multiple modelling approach for non-linear and non-stationary systems

This paper proposes a novel adaptive multiple modelling algorithm for non-linear and non-stationary systems. This simple modelling paradigm comprises K candidate sub-models which are all linear. With data available in an online fashion, the performance of all candidate sub-models are monitored based on the most recent data window, and M best sub-models are selected from the K candidates. The weight coefficients of the selected sub-model are adapted via the recursive least square (RLS) algorithm, while the coefficients of the remaining sub-models are unchanged. These M model predictions are then optimally combined to produce the multi-model output. We propose to minimise the mean square error based on a recent data window, and apply the sum to one constraint to the combination parameters, leading to a closed-form solution, so that maximal computational efficiency can be achieved. In addition, at each time step, the model prediction is chosen from either the resultant multiple model or the best sub-model, whichever is the best. Simulation results are given in comparison with some typical alternatives, including the linear RLS algorithm and a number of online non-linear approaches, in terms of modelling performance and time consumption.     

The data-based mechanistic approach to the modelling, forecasting and control of environmental systems

The paper presents a unified approach to the modelling, forecasting and control of natural and man-made environmental systems. The modelling approach exploits the author’s Data-Based Mechanistic (DBM) modelling philosophy, combined with powerful methods of recursive statistical estimation. These provide the basis for two major stages of model building: first, the critical evaluation of the over-parametrized simulation models that are currently the most common vehicle used in environmental planning and management studies; and second, the adaptive, data-based estimation of parsimonious, ‘top-down’ models that can be used for adaptive forecasting and data assimilation, as well as operational control and management system design. The associated control system design methodology is based on the Non-Minimal State Space (NMSS) approach to the design of Proportional-Integral-Plus (PIP) control systems, based on the DBM models obtained at the previous modelling stage. The paper includes a case study concerned with the modelling and control of globally averaged levels of CO₂ in the atmosphere.     

A sketch-based approach to human body modelling

In this paper, we present a new approach and a novel interface, Virtual Human Sketcher (VHS), which enables those who can draw, to sketch-out various human body models. Our approach supports freehand drawing input and a “Stick Figure→Fleshing-out→Skin Mapping” modelling pipeline. Following this pipeline, a stick figure is drawn first to illustrate a figure pose, which is automatically reconstructed into 3D through a “Multi-layered Back-Front Ambiguity Clarifier”. It is then fleshed-out with freehand body contours. A “Creative Model-based Method” is developed for interpreting the body size, shape, and fat distribution of the sketched figure and transferring it into a 3D human body through graphical comparisons and generic model morphing. The generic model is encapsulated with three distinct layers: skeleton, fat tissue, and skin. It can be transformed sequentially through rigid morphing, fatness morphing, and surface matching to match the 2D figure sketch. The initial resulting 3D body model can be incrementally modified through sketching directly on the 3D model. In addition, this body surface can be mapped onto a series of posed stick figures to be interpolated as a 3D character animation. VHS has been tested by various users on Tablet PC. After minimal training, even a beginner can create plausible human bodies and animate them within minutes.     

Protocol modelling: A modelling approach that supports reusable behavioural abstractions

We describe a behavioural modelling approach based on the concept of a “Protocol Machine”, a machine whose behaviour is governed by rules that determine whether it accepts or refuses events that are presented to it. We show how these machines can be composed in the manner of mixins to model object behaviour and show how the approach provides a basis for defining reusable fine-grained behavioural abstractions. We suggest that this approach provides better encapsulation of object behaviour than traditional object modelling techniques when modelling transactional business systems. We relate the approach to work going on in model driven approaches, specifically the Model Driven Architecture initiative sponsored by the Object Management Group. Communicated by August-Wilhelm Scheer Ashley McNeile is a practitioner with over 25 years of experience in systems development and IT related management consultancy. His main areas of interest are requirements analysis techniques and model execution and in 2001 he founded Metamaxim Ltd. to pioneer new techniques in these areas. He has published and presented widely on object oriented development methodology and systems architecture. Nicholas Simons has been working with formal methods of system specification since their introduction, and has over 20 years experience in building tools for system design, code generation and reverse engineering. In addition, he lectures on systems analysis and design, Web programming and project planning. He is a co-founder and director of Metamaxim Ltd.     

A Quasi-ARMAX approach to modelling of non-linear systems

This paper proposes a class of quasi-ARMAX models for non-linear systems. Similar to ordinary non-linear ARMAX models, the quasi-ARMAX models are flexible black-box models, but they have various linearity properties similar to those of linear ARMAX models. A modelling scheme is introduced to construct models consisting of two parts: a macro-part and a kernel-part. By using Taylor expansion and other mathematical transformation techniques, it is first constructed as a class of quasi-ARMAX interfaces (macro-parts) that have various linearity properties but contain some complicated coefficients. MIMO neurofuzzy models (kernel-parts) are then introduced to represent the complicated coefficients. It is shown that the proposed quasi-ARMAX models have both good approximation ability and some easy-to-use properties. The proposed models have been successfully applied to prediction, fault detection and adaptive control of non-linear systems.     

A unified approach to Markov decision problems and performance sensitivity analysis with discounted and average criteria: multichain cases

We propose a unified framework to Markov decision problems and performance sensitivity analysis for multichain Markov processes with both discounted and average-cost performance criteria. With the fundamental concept of performance potentials, we derive both performance-gradient and performance-difference formulas, which play the central role in performance optimization. The standard policy iteration algorithms for both discounted- and average-reward MDPs can be established using the performance-difference formulas in a simple and intuitive way; and the performance-gradient formulas together with stochastic approximation may lead to new optimization schemes. This sensitivity-based point of view of performance optimization provides some insights that link perturbation analysis, Markov decision processes, and reinforcement learning together. The research is an extension of the previous work on ergodic Markov chains (Cao, Automatica 36 (2000) 771).     

A bilinear differential forms approach to parametric structured state-space modelling

We use one-variable Loewner techniques to compute polynomial-parametric models for MIMO systems from vector-exponential data gathered at various points in the parameter space. Instrumental in our approach are the connections between vector-exponential modelling via bilinear differential forms and the Loewner framework.     

A unified approach to adapt scientific visualization systems to third-party solvers

This paper presents a new unified approach to adapt scientific visualization systems to third-party solvers implemented on different software and hardware platforms. This approach allows building multiplatform visualization systems, enables automatic conversion of input and output data from any solver into a rendering-compatible format, and provides real-time generation of high-quality images. The automated adaptation of visualization systems to third-party solvers is based on ontological engineering methods. Multiplatform portability is provided by the automatic generation of a graphical user interface (GUI) for each particular operating system and by preprocessing the data to be rendered by using heuristic-based tools, which ensures compatibility with different hardware and software platforms, including desktop computers and mobile devices. In addition, an original anti-aliasing algorithm is proposed to ensure high quality of resulting images. Based on the proposed approach, a multiplatform scientific visualization system called SciVi is developed, which is successfully used for solving various real-world scientific visualization problems from different application domains.     

A practical approach to data modelling in spatial applications

The storage and manipulation of spatial data requires a different style of support from that normally found in commercial database systems. This paper explores the use of the functional data model and the high level language Daplex to provide an integrated tool for the conceptual modelling of spatial data and the manipulation of data values. Importance is attached to allowing dynamic schema definition and to the provision of abstract data types to support spatial objects. The implementation comprises three separate modules and uses an underlying relational DBMS to store all metadata and data values. This modular design has enabled the user interface, Daplex language and storage aspects of the software to be developed independently, creating a system which has already proved to be easily portable. Consideration has also been given to ways of improving system performance.