A comparative assessment of collaborative business process verification approaches.

Industry 4.0 is a key strategic trend of the economy. Virtual factories are key building blocks for Industry 4.0 where product design processes, manufacturing processes and general collaborative business processes across factories and enterprises are integrated. In the context of EU H2020 FIRST (vF Interoperation suppoRting buSiness innovaTion) project, end users of vFs are not experts in business process modelling to guarantee correct collaborative business processes for realizing execution. To enable automatic execution of business processes, verification is an important step at the business process design stage to avoid errors at runtime. Research in business process model verification has yielded a plethora of approaches in form of languages and tools that are based on Petri nets family and temporal logic. However, no report specifically targets and presents a comparative assessment of these approaches based on criteria as one we propose. In this paper we present an assessment of the most common verification approaches based on their expressibility, flexibility, suitability and complexity. We also look at how big data impacts the business process verification approach in a data-rich world

Multi-tier agent architecture for open service ecosystems

Proceeding volume: Vol-918Peer reviewe

Estimating and Measuring Application Latency of Typical Distributed Interactive Simulation (DIS) - Based Simulation Architecture

One of the challenges in a distributed virtual environment stems from the requirement to simultaneously execute the simulations in realtime to support human interaction, in conjunction with maintaining a consistent view of the shared simulated environment. Maintaining a consistent set of simulation state data in the presence of network latency is difficult if individual data items are updated frequently. The principle application of DIS-based simulation environments has been in the domain of training where a consistent view or its correctness is often judged in subjective terms such as the simulation looking and feeling correct. New application areas for these systems are emerging in the analysis and test domains. For these domains, quantifying shared state consistency in terms of overall distributed application architecture is desirable. This research effort will investigate and validate methods to calculate and measure the latency effects that consider the structure of the applications themselves. Additional latencies introduced due to the software architecture may significantly affect the consistency of the simulation. An improved understanding is beneficial to the Air Force where real-time distributed simulations used for the purpose of analyzing the systems they simulate and the support of live test events

A model-based approach to System of Systems risk management

The failure of many System of Systems (SoS) enterprises can be attributed to the inappropriate application of traditional Systems Engineering (SE) processes within the SoS domain, because of the mistaken belief that a SoS can be regarded as a single large, or complex, system. SoS Engineering (SoSE) is a sub-discipline of SE; Risk Management and Modelling and Simulation (M&S) are key areas within SoSE, both of which also lie within the traditional SE domain. Risk Management of SoS requires a different approach to that currently taken for individual systems; if risk is managed for each component system then it cannot be assumed that the aggregated affect will be to mitigate risk at the SoS level. A literature review was undertaken examining three themes: (1) SoS Engineering (SoSE), (2) M&S and (3) Risk. Theme 1 of the literature provided insight into the activities comprising SoSE and its difference from traditional SE with risk management identified as a key activity. The second theme discussed the application of M&S to SoS, providing an output, which supported the identification of appropriate techniques and concluding that, the inherent complexity of a SoS required the use of M&S in order to support SoSE activities. Current risk management approaches were reviewed in theme 3 as well as the management of SoS risk. Although some specific examples of the management of SoS risk were found, no mature, general approach was identified, indicating a gap in current knowledge. However, it was noted most of these examples were underpinned by M&S approaches. It was therefore concluded a general approach SoS risk management utilising M&S methods would be of benefit. In order to fill the gap identified in current knowledge, this research proposed a new model based approach to Risk Management where risk identification was supported by a framework, which combined SoS system of interest dimensions with holistic risk types, where the resulting risks and contributing factors are captured in a causal network. Analysis of the causal network using a model technique selection tool, developed as part of this research, allowed the causal network to be simplified through the replacement of groups of elements within the network by appropriate supporting models. The Bayesian Belief Network (BBN) was identified as a suitable method to represent SoS risk. Supporting models run in Monte Carlo Simulations allowed data to be generated from which the risk BBNs could learn, thereby providing a more quantitative approach to SoS risk management. A method was developed which provided context to the BBN risk output through comparison with worst and best-case risk probabilities. The model based approach to Risk Management was applied to two very different case studies: Close Air Support mission planning and the Wheat Supply Chain, UK National Food Security risks, demonstrating its effectiveness and adaptability. The research established that the SoS SoI is essential for effective SoS risk identification and analysis of risk transfer, effective SoS modelling requires a range of techniques where suitability is determined by the problem context, the responsibility for SoS Risk Management is related to the overall SoS classification and the model based approach to SoS risk management was effective for both application case studies

Overview on agent-based social modelling and the use of formal languages

Transdisciplinary Models and Applications investigates a variety of programming languages used in validating and verifying models in order to assist in their eventual implementation. This book will explore different methods of evaluating and formalizing simulation models, enabling computer and industrial engineers, mathematicians, and students working with computer simulations to thoroughly understand the progression from simulation to product, improving the overall effectiveness of modeling systems.Postprint (author's final draft

Development and Specification of Virtual Environments

This thesis concerns the issues involved in the development of virtual environments (VEs). VEs are more than virtual reality. We identify four main characteristics of them: graphical interaction, multimodality, interface agents, and multi-user. These characteristics are illustrated with an overview of different classes of VE-like applications, and a number of state-of-the-art VEs. To further define the topic of research, we propose a general framework for VE systems development, in which we identify five major classes of development tools: methodology, guidelines, design specification, analysis, and development environments. Of each, we give an overview of existing best practices