Automated Customer-Centric Performance Analysis of Generalised Stochastic Petri Nets Using Tagged Tokens

Since tokens in Generalised Stochastic Petri Net (GSPN) models are indistinguishable, it is not always possible to reason about customer-centric performance measures. To remedy this, we propose tagged tokens - a variant of the tagged customer technique used in the analysis of queueing networks. Under this scheme, one token in a structurally restricted net is tagged and its position tracked as it moves around the net. Performance queries can then be phrased in terms of the position of the tagged token. To date, the tagging of customers or tokens has been a time-consuming, manual and model-specific process. By contrast, we present here a completely automated methodology for the tagged token analysis of GSPNs. We first describe an intuitive graphical means of specifying the desired tagging configuration, along with the constraints on GSPN structure which must be observed for tagged tokens to be incorporated. We then present the mappings required for automatically converting a GSPN with a user-specified tagging structure into a Coloured GSPN (CGSPN), and thence into an unfolded GSPN which can be analysed for performance measures of interest by existing tools. We further show how our methodology integrates with Performance Trees, a formalism for the specification of performance queries. We have implemented our approach in the open source PIPE Petri net tool, and use this to illustrate the extra expressibility granted by tagged tokens through the analysis of a GSPN model of a hospitals Accident and Emergency department. © 2009 Elsevier B.V. All rights reserved

Performance requirements verification during software systems development

Requirements verification refers to the assurance that the implemented system reflects the specified requirements. Requirement verification is a process that continues through the life cycle of the software system. When the software crisis hit in 1960, a great deal of attention was placed on the verification of functional requirements, which were considered to be of crucial importance. Over the last decade, researchers have addressed the importance of integrating non-functional requirement in the verification process. An important non-functional requirement for software is performance. Performance requirement verification is known as Software Performance Evaluation. This thesis will look at performance evaluation of software systems. The performance evaluation of software systems is a hugely valuable task, especially in the early stages of a software project development. Many methods for integrating performance analysis into the software development process have been proposed. These methodologies work by utilising the software architectural models known in the software engineering field by transforming these into performance models, which can be analysed to gain the expected performance characteristics of the projected system. This thesis aims to bridge the knowledge gap between performance and software engineering domains by introducing semi-automated transformation methodologies. These are designed to be generic in order for them to be integrated into any software engineering development process. The goal of these methodologies is to provide performance related design guidance during the system development. This thesis introduces two model transformation methodologies. These are the improved state marking methodology and the UML-EQN methodology. It will also introduce the UML-JMT tool which was built to realise the UML-EQN methodology. With the help of automatic design models to performance model algorithms introduced in the UML-EQN methodology, a software engineer with basic knowledge of performance modelling paradigm can conduct a performance study on a software system design. This was proved in a qualitative study where the methodology and the tool deploying this methodology were tested by software engineers with varying levels of background, experience and from different sectors of the software development industry. The study results showed an acceptance for this methodology and the UML-JMT tool. As performance verification is a part of any software engineering methodology, we have to define frame works that would deploy performance requirements validation in the context of software engineering. Agile development paradigm was the result of changes in the overall environment of the IT and business worlds. These techniques are based on iterative development, where requirements, designs and developed programmes evolve continually. At present, the majority of literature discussing the role of requirements engineering in agile development processes seems to indicate that non-functional requirements verification is an unchartered territory. CPASA (Continuous Performance Assessment of Software Architecture) was designed to work in software projects where the performance can be affected by changes in the requirements and matches the main practices of agile modelling and development. The UML-JMT tool was designed to deploy the CPASA Performance evaluation tests

Process Mining Handbook

This is an open access book. This book comprises all the single courses given as part of the First Summer School on Process Mining, PMSS 2022, which was held in Aachen, Germany, during July 4-8, 2022. This volume contains 17 chapters organized into the following topical sections: Introduction; process discovery; conformance checking; data preprocessing; process enhancement and monitoring; assorted process mining topics; industrial perspective and applications; and closing

Scalable Performance Analysis of Massively Parallel Stochastic Systems

The accurate performance analysis of large-scale computer and communication systems is directly inhibited by an exponential growth in the state-space of the underlying Markovian performance model. This is particularly true when considering massively-parallel architectures such as cloud or grid computing infrastructures. Nevertheless, an ability to extract quantitative performance measures such as passage-time distributions from performance models of these systems is critical for providers of these services. Indeed, without such an ability, they remain unable to offer realistic end-to-end service level agreements (SLAs) which they can have any confidence of honouring. Additionally, this must be possible in a short enough period of time to allow many different parameter combinations in a complex system to be tested. If we can achieve this rapid performance analysis goal, it will enable service providers and engineers to determine the cost-optimal behaviour which satisfies the SLAs. In this thesis, we develop a scalable performance analysis framework for the grouped PEPA stochastic process algebra. Our approach is based on the approximation of key model quantities such as means and variances by tractable systems of ordinary differential equations (ODEs). Crucially, the size of these systems of ODEs is independent of the number of interacting entities within the model, making these analysis techniques extremely scalable. The reliability of our approach is directly supported by convergence results and, in some cases, explicit error bounds. We focus on extracting passage-time measures from performance models since these are very commonly the language in which a service level agreement is phrased. We design scalable analysis techniques which can handle passages defined both in terms of entire component populations as well as individual or tagged members of a large population. A precise and straightforward specification of a passage-time service level agreement is as important to the performance engineering process as its evaluation. This is especially true of large and complex models of industrial-scale systems. To address this, we introduce the unified stochastic probe framework. Unified stochastic probes are used to generate a model augmentation which exposes explicitly the SLA measure of interest to the analysis toolkit. In this thesis, we deploy these probes to define many detailed and derived performance measures that can be automatically and directly analysed using rapid ODE techniques. In this way, we tackle applicable problems at many levels of the performance engineering process: from specification and model representation to efficient and scalable analysis

Predicting software performance in symmetric multi-core and multiprocessor Environments

With today\u27s rise of multi-core processors, concurrency becomes a ubiquitous challenge in software development.Performance prediction methods have to reflect the influence of multiprocessing environments on software performance in order to help software architects to find potential performance problems during early development phases. In this thesis, we address the influence of the operating system scheduler on software performance in symmetric multiprocessing environments

Process Mining Workshops

This open access book constitutes revised selected papers from the International Workshops held at the Third International Conference on Process Mining, ICPM 2021, which took place in Eindhoven, The Netherlands, during October 31–November 4, 2021. The conference focuses on the area of process mining research and practice, including theory, algorithmic challenges, and applications. The co-located workshops provided a forum for novel research ideas. The 28 papers included in this volume were carefully reviewed and selected from 65 submissions. They stem from the following workshops: 2nd International Workshop on Event Data and Behavioral Analytics (EDBA) 2nd International Workshop on Leveraging Machine Learning in Process Mining (ML4PM) 2nd International Workshop on Streaming Analytics for Process Mining (SA4PM) 6th International Workshop on Process Querying, Manipulation, and Intelligence (PQMI) 4th International Workshop on Process-Oriented Data Science for Healthcare (PODS4H) 2nd International Workshop on Trust, Privacy, and Security in Process Analytics (TPSA) One survey paper on the results of the XES 2.0 Workshop is included

Process Mining Workshops

This open access book constitutes revised selected papers from the International Workshops held at the Third International Conference on Process Mining, ICPM 2021, which took place in Eindhoven, The Netherlands, during October 31–November 4, 2021. The conference focuses on the area of process mining research and practice, including theory, algorithmic challenges, and applications. The co-located workshops provided a forum for novel research ideas. The 28 papers included in this volume were carefully reviewed and selected from 65 submissions. They stem from the following workshops: 2nd International Workshop on Event Data and Behavioral Analytics (EDBA) 2nd International Workshop on Leveraging Machine Learning in Process Mining (ML4PM) 2nd International Workshop on Streaming Analytics for Process Mining (SA4PM) 6th International Workshop on Process Querying, Manipulation, and Intelligence (PQMI) 4th International Workshop on Process-Oriented Data Science for Healthcare (PODS4H) 2nd International Workshop on Trust, Privacy, and Security in Process Analytics (TPSA) One survey paper on the results of the XES 2.0 Workshop is included

Application of Optimization in Production, Logistics, Inventory, Supply Chain Management and Block Chain

The evolution of industrial development since the 18th century is now experiencing the fourth industrial revolution. The effect of the development has propagated into almost every sector of the industry. From inventory to the circular economy, the effectiveness of technology has been fruitful for industry. The recent trends in research, with new ideas and methodologies, are included in this book. Several new ideas and business strategies are developed in the area of the supply chain management, logistics, optimization, and forecasting for the improvement of the economy of the society and the environment. The proposed technologies and ideas are either novel or help modify several other new ideas. Different real life problems with different dimensions are discussed in the book so that readers may connect with the recent issues in society and industry. The collection of the articles provides a glimpse into the new research trends in technology, business, and the environment

Expanding the Horizons of Manufacturing: Towards Wide Integration, Smart Systems and Tools

This research topic aims at enterprise-wide modeling and optimization (EWMO) through the development and application of integrated modeling, simulation and optimization methodologies, and computer-aided tools for reliable and sustainable improvement opportunities within the entire manufacturing network (raw materials, production plants, distribution, retailers, and customers) and its components. This integrated approach incorporates information from the local primary control and supervisory modules into the scheduling/planning formulation. That makes it possible to dynamically react to incidents that occur in the network components at the appropriate decision-making level, requiring fewer resources, emitting less waste, and allowing for better responsiveness in changing market requirements and operational variations, reducing cost, waste, energy consumption and environmental impact, and increasing the benefits. More recently, the exploitation of new technology integration, such as through semantic models in formal knowledge models, allows for the capture and utilization of domain knowledge, human knowledge, and expert knowledge toward comprehensive intelligent management. Otherwise, the development of advanced technologies and tools, such as cyber-physical systems, the Internet of Things, the Industrial Internet of Things, Artificial Intelligence, Big Data, Cloud Computing, Blockchain, etc., have captured the attention of manufacturing enterprises toward intelligent manufacturing systems

Second Generation General System Theory: Perspectives in Philosophy and Approaches in Complex Systems

Following the classical work of Norbert Wiener, Ross Ashby, Ludwig von Bertalanffy and many others, the concept of System has been elaborated in different disciplinary fields, allowing interdisciplinary approaches in areas such as Physics, Biology, Chemistry, Cognitive Science, Economics, Engineering, Social Sciences, Mathematics, Medicine, Artificial Intelligence, and Philosophy. The new challenge of Complexity and Emergence has made the concept of System even more relevant to the study of problems with high contextuality. This Special Issue focuses on the nature of new problems arising from the study and modelling of complexity, their eventual common aspects, properties and approaches—already partially considered by different disciplines—as well as focusing on new, possibly unitary, theoretical frameworks. This Special Issue aims to introduce fresh impetus into systems research when the possible detection and correction of mistakes require the development of new knowledge. This book contains contributions presenting new approaches and results, problems and proposals. The context is an interdisciplinary framework dealing, in order, with electronic engineering problems; the problem of the observer; transdisciplinarity; problems of organised complexity; theoretical incompleteness; design of digital systems in a user-centred way; reaction networks as a framework for systems modelling; emergence of a stable system in reaction networks; emergence at the fundamental systems level; behavioural realization of memoryless functions