On Proposing Statecharts to Specify Performance Models

This paper shows that Statecharts, a high-level specification technique, can be used to represent performance models. This is a powerful technique and is based on state-transition diagrams added with concepts of hierarchy and orthogonality to represent a system behavior. It is shown that Statecharts may conveniently be used to represent models with richness and clarity. Using an analytical approach the technique to determine performance measurements is provided. Three examples are presented and the results show Statecharts' potential for representing systems for performance evaluation.     

A performance model for analysis of heterogeneous multi-cluster systems

This paper addresses the problem of performance modeling for large-scale heterogeneous distributed systems with emphases on multi-cluster computing systems. Since the overall performance of distributed systems is often depends on the effectiveness of its communication network, the study of the interconnection networks for these systems is very important. Performance modeling is required to avoid poorly chosen components and architectures as well as discovering a serious shortfall during system testing just prior to deployment time. However, the multiplicity of components and associated complexity make performance analysis of distributed computing systems a challenging task. To this end, we present an analytical performance model for the interconnection networks of heterogeneous multi-cluster systems. The analysis is based on a parametric family of fat-trees, the m-port n-tree, and a deterministic routing algorithm, which is proposed in this paper. The model is validated through comprehensive simulation, which demonstrated that the proposed model exhibits a good degree of accuracy for various system organizations and under different working conditions.     

Parametric probabilistic transition systems for system design and analysis

We develop a model of parametric probabilistic transition Systems (PPTSs), where probabilities associated with transitions may be parameters. We show how to find instances of the parameters that satisfy a given property and instances that either maximize or minimize the probability of reaching a certain state. As an application, we model a probabilistic non-repudiation protocol with a PPTS. The theory we develop allows us to find instances that maximize the probability that the protocol ends in a fair state (no participant has an advantage over the others). A preliminary version of this paper was presented at SEFM’04 [LMT04]. 05 April 2006     

An approximate model for performance evaluation of real-time multimedia communication systems

A Markov Modulated Poisson Process (MMPP) is a doubly stochastic Poisson process which has recently received a lot of attention due to its ability to model a highly correlated arrival stream while retaining analytical tractability. In this paper, the cell arrival process from integrated voice and data sources is approximated by a two-state MMPP with batch arrivals (BMMPP). We propose a new matching technique which leads to more accurate performance prediction than other recent work for both delay estimation and evaluation of tail probabilities. While using BMMPP in the model does not noticeably increase the computational complexity over MMPP, it allows better representation of traffic sources with significantly higher burstiness. Another major contribution of the proposed model is its simplicity which makes the model suitable for real-time traffic control. An extended version of the model for integrated video, voice and data sources is also given with numerical examples again showing that the accuracy is quite satisfactory.     

Patient flow modelling and performance analysis of healthcare delivery processes in hospitals: A review and reflections

Analysis of hospital processes is essential for development of improved methods, policies and decision tools for overall performance improvement of the hospital system. Amidst the current scenario of continuously increasing healthcare costs and scarcity of resources, optimal utilization of resources without hampering the quality of care has gained importance in any country. Modelling, analysis and management of patient flows, in this context, plays a key role in performance analysis and improvement of hospital processes as appropriate modelling of patient flows may help healthcare managers make decisions related to capacity planning, resource allocation and scheduling, appointment scheduling and for making necessary changes in the process of care. The concept of patient flow and its modelling has gained much attention in healthcare management literature over past few decades. In this paper, the existing approaches pertaining to modelling of patient flows in hospital systems have been classified and critically appraised focussing on the recent advancements in order to identify future research avenues. A generic framework for patient flow modelling and performance analysis of hospital systems that may serve as a guide for the practitioners dealing with similar kinds of problems to improve healthcare delivery has also been provided.     

Moments of accumulated reward and completion time in Markovian models with application to unreliable manufacturing systems

Performance evaluation models are used by companies to design, adapt, manage and control their production systems. In the literature, most of the effort has been dedicated to the development of efficient methodologies to estimate the first moment performance measures of production systems, such as the expected production rate, the buffer levels and the mean completion time. However, there is industrial evidence that the higher moments of the production output may drastically impact on the capability of managing the system operations, causing the observed system performance to be highly different from what expected. This paper presents a methodology to analyze the cumulated output and the lot completion time moments of Markovian reward models. Both the discrete and continuous time cases are considered. The technique is applied to unreliable manufacturing systems characterized by general Markovian structures. Numerical results show how the theory developed in this paper can be applied to analyse the dependency of the output variability and the service level on the system parameters. Moreover, they highlight previously uninvestigated features of the system behavior that are useful while operating the system in practical settings.     

Early quality monitoring in the development of real-time reactive systems

The increasing trend toward complex software systems has highlighted the need to incorporate quality requirements earlier in the development cycle. We propose a new methodology for monitoring quality in the earliest phases of real-time reactive system (RTRS) development. The targeted quality characteristics are functional complexity, performance, reliability, architectural complexity, maintainability, and test coverage. All these characteristics should be continuously monitored throughout the RTRS development cycle, to provide decision support and detect the first signs of low or decreasing quality as the system design evolves. The ultimate goal of this methodology is to assist developers in dealing with complex user requirements and ensure that the formal development process yields a high-quality application. Each aspect of quality monitoring is formalized mathematically and illustrated using a train-gate-controller case study.     

Extending the information delivery manual approach to identify information requirements for performance analysis of HVAC systems

Heating, Ventilation and Air-Conditioning (HVAC) systems account for more than 15% of the total energy consumption in the US. In order to improve the energy efficiency of HVAC systems, researchers have developed hundreds of algorithms to automatically analyze their performance. However, the complex information, such as configurations of HVAC systems, layouts and materials of building elements and dynamic data from the control systems, required by these algorithms inhibits the process of deploying them in real-world facilities. To address this challenge, we envision a framework that automatically integrates the required information items and provides them to the performance analysis algorithms for HVAC systems. This paper presents an approach to identify and document the information requirements from the publications that describe these algorithms. We extend the Information Delivery Manual (IDM) approach so that the identified information requirements can be mapped to multiple information sources that use various formats and schemas. This paper presents the extensions to the IDM approach and the results of using it to identify information requirements for performance analysis algorithms of HVAC systems.     

An analysis of the exponential decay principle in probabilistic trust models

Research in models for experience-based trust management has either ignored the problem of modelling and reasoning about dynamically changing principal behaviour, or provided ad hoc solutions to it. Probability theory provides a foundation for addressing this and many other issues in a rigorous and mathematically sound manner. Using Hidden Markov Models to represent principal behaviours, we focus on computational trust frameworks based on the ‘beta’ probability distribution and the principle of exponential decay, and derive a precise analytical formula for the estimation error they induce. This allows potential adopters of beta-based computational trust frameworks and algorithms to better understand the implications of their choice.     

Markov-chain model and algorithmic procedure for the performance analysis of closed cyclic queues

This paper presents a model and an algorithmic procedure to analyze closed cyclic queues that are subject to blocking. We consider the first two moments of the processing time and present the fitting of phase-type distributions such that the number of phases and transitions is minimal. Using phase-type distributions, we enable the analysis of queueing systems with processing times with any coefficient of variation. We model the closed cyclic queues subject to blocking as continuous-time Markov chains. The implementation procedure covers the state-space generation and the determination of the infinitesimal generator matrix. Apart from rounding errors, we obtain exact results for the queueing model this way. The results are useful as reference values for the output of approximate approaches. Further, the algorithmic procedure enables a repeated analysis of different configuration alternatives as needed in optimization procedures. Though the method is very fast for small cyclic queues, it takes a long computation time for larger systems. Furthermore, the size of the queueing model to be analyzed is restricted due to the limited working memory with its present-day capacity. In a numerical study, the computation times for different configurations are investigated, limits in the size of the applicable queueing model are given, and numerical results of the performance measures are provided.     

Modelling and performance analysis of inter-processor messaging in distributed systems

This paper addresses some performance modelling issues arising from the inter-processor messaging requirements of distributed real-time processing systems. We consider two basic classes of message transfer protocols, namely clocked schemes where message transfer is initiated as a periodic timed task, and event-driven schemes where the transfer mechanism is triggered by the messaging requests themselves. The aim is to maximize system efficiency by passing messages in batches. It is shown how the classes of protocols may be modelled by a two-stage queueing systems, which is analysed using the theory of imbedded Markov chains and semi-Markov processes. The results are used to show how the important performance measures are derived, and how the protocol parameters should be chosen to optimize the overall message system performance. The methods are illustrated by numerical examples.     

Performability analysis of computer systems: from model specification to solution

Computer systems reliability/availability modeling deals with the representation of changes in the structure of the system being modeled, which are generally due to faults, and how such changes affect the availability of the system. On the other hand, performance modeling involves representing the probabilistic nature of user demands and predicting the system capacity to perform useful work, under the assumption that the system structure remains constant. With the advent of degradable systems, the system may be restructured in response to faults and may continue to perform useful work, even though operating at lower capacity. Performability modeling considers the effect of structural changes and their impact on the overall performance of the system. The complexity of current computer systems and the variety of different problems to be analyzed, including the simultaneous evaluation of performance and availability, demonstrate the need for sophisticated tools that allow the specification of general classes of problems while incorporating powerful analytic and/or simulation techniques. Concerning model specification, a recently proposed object oriented modeling paradigm that accommodates a wide variety of applications is discussed and compared with other approaches. With respect to solution methods, a brief overview of past work on performability evaluation of Markov models is presented. Then it is shown that many performability related measures can be calculated using the uniformization or randomization technique by coloring distinguished states and/or transitions of the Markov model of the system being studied. Finally, the state space explosion problem is addressed and several techniques for dealing with the problem are discussed.     

Dynamic adaptation of response-time models for QoS management in autonomic systems

In transactional systems, the objectives of quality of service regarding are often specified by Service Level Objectives (SLOs) that stipulate a response time to be achieved for a percentile of the transactions. Usually, there are different client classes with different SLOs. In this paper, we extend a technique that enforces the fulfilment of the SLOs using admission control. The admission control of new user sessions is based on a response-time model. The technique proposed in this paper dynamically adapts the model to changes in workload characteristics and system configuration, so that the system can work autonomically, without human intervention. The technique requires no knowledge about the internals of the system; thus, it is easy to use and can be applied to many systems. Its utility is demonstrated by a set of experiments on a system that implements the TPC-App benchmark. The experiments show that the model adaptation works correctly in very different situations that include large and small changes in response times, increasing and decreasing response times, and different patterns of workload injection. In all this scenarios, the technique updates the model progressively until it adjusts to the new situation and in intermediate situations the model never experiences abnormal behaviour that could lead to a failure in the admission control component.     

False alarm moderation for performance monitoring in industrial water distribution systems

While considerable attention has been given to data driven methods that analyse and control energy systems in buildings, the same cannot be said for building water systems. As a result, approaches which support enhanced efficiency in building water consumption are somewhat underdeveloped, particularly in industrial settings. Water consumption in industrial systems features non-stationarity (i.e., variations in statistical properties over time), making it challenging to distinguish between routine and non-routine water uses. In such scenarios, fault detection and diagnosis methods that leverage multivariate statistical process control with, for example, principal component analysis and detection indices (Hotelling T²-statistics and Q-statistics), can be successfully used to identify system alarms. However, even with these approaches there can be a high prevalence of false alarms leading to low industry uptake of fault detection and diagnosis systems, or where in place, alarms can be ignored. To efficiently detect and diagnose water distribution system faults, false alarms should be controlled through false alarm moderation approaches so that building managers/operators only need to focus on critical system alarms or system alarms with high risk levels. This paper utilises two statistical non-parametric false alarm moderation approaches (window-based, and trial-based) that generate a second control limit for T²-statistics and Q-statistics. The implementation of these false alarm moderation approaches was combined with principal component analysis to detect faults with real water time series data from two case-study sites. Using both approaches false alarms were reduced, and the overall performance and reliability of the fault detection and diagnosis approach was improved. The principal component analysis model with the window-based approach was shown to be particularly effective.     

Observers for a class of Lipschitz systems with extension to performance analysis

In this paper, observer design for a class of Lipschitz nonlinear dynamical systems is investigated. One of the main contributions lies in the use of the differential mean value theorem (DMVT) which allows transforming the nonlinear error dynamics into a linear parameter varying (LPV) system. This has the advantage of introducing a general Lipschitz-like condition on the Jacobian matrix for differentiable systems. To ensure asymptotic convergence, in both continuous and discrete time systems, such sufficient conditions expressed in terms of linear matrix inequalities (LMIs) are established. An extension to H_∞ filtering design is obtained also for systems with nonlinear outputs. A comparison with respect to the observer method of Gauthier et al. [A simple observer for nonlinear systems. Applications to bioreactors, IEEE Trans. Automat. Control 37(6) (1992) 875–880] is presented to show that the proposed approach avoids high gain for a class of triangular globally Lipschitz systems. In the last section, academic examples are given to show the performances and some limits of the proposed approach. The last example is introduced with the goal to illustrate good performances on robustness to measurement errors by avoiding high gain.     

Managing database server performance to meet QoS requirements in electronic commerce systems

The performance of electronic commerce systems has a major impact on their acceptability to users. Different users also demand different levels of performance from the system, that is, they will have different Quality of Service (QoS) requirements. Electronic commerce systems are the integration of several different types of servers and each server must contribute to meeting the QoS demands of the users. In this paper we focus on the role, and the performance, of a database server within an electronic commerce system. We examine the characteristics of the workload placed on a database server by an electronic commerce system and suggest a range of QoS requirements for the database server based on this analysis of the workload. We argue that a database server must be able to dynamically reallocate its resources in order to meet the QoS requirements of different transactions as the workload changes. We describe Quartermaster, which is a system to support dynamic goal-oriented resource management in database management systems, and discuss how it can be used to help meet the QoS requirements of the electronic commerce database server. We provide an example of the use of Quartermaster that illustrates how the dynamic reallocation of memory resources can be used to meet the QoS requirements of a set of transactions similar to transactions found in an electronic commerce workload. We briefly describe the memory reallocation algorithms used by Quartermaster and present experiments to show the impact of the reallocations on the performance of the transactions. Published online: 22 August 2001