Proceedings, MSVSCC 2018

Proceedings of the 12th Annual Modeling, Simulation & Visualization Student Capstone Conference held on April 19, 2018 at VMASC in Suffolk, Virginia. 155 pp

Effect of Industry 4.0 on Education Systems: An Outlook

Congreso Universitario de Innovación Educativa En las Enseñanzas Técnicas, CUIEET (26º. 2018. Gijón

Task scheduling for application integration: A strategy for large volumes of data

Enterprise Application Integration is the research field, which provides methodologies, techniques and tools for modelling and implementing integration processes. An integration process performs the orchestration of a set of applications to keep them synchronised or to allow the creation of new features. It can be represented by a workflow composed of tasks and communication channels. Integration platforms are tools for the design and execution of integration processes in which, the runtime system is the component responsible for execution time of the tasks and the allocation of computational resources that perform them. The processing of a large volume of data, corresponding to execution of millions of tasks, can cause situations of overload, characterised by the accumulation of tasks in internal queues awaiting computational resources in the runtime systems, resulting in unacceptable response time for the external applications and users. Our research hypothesis is that the runtime systems of the integration platforms use simplistic heuristics for scheduling tasks, which does not allow them to maintain acceptable levels of performance when there are overload situations. In this research work, we developed (i) a representation for integration processes, (ii) a characterisation for your task schedules, (iii) a heuristic to deal with situations of overload, (iv) a mathematical model for a performance metric of the execution of integration processes and (v) a simulation tool for task scheduling heuristics. Our research results indicate that, in situations of overload, our heuristic promotes a balanced workload distribution and an increase in the performance of the execution of the integration processes.Integração de Aplicações Empresariais é o campo de pesquisa, que fornece metodologias, técnicas e ferramentas para modelar e implementar processos de integração. Um processo de integração executa a orquestração de um conjunto de aplicações para mantê-las sincronizadas ou para permitir a criação de novas funcionalidades. Ele pode ser representado por um fluxo de trabalho composto por tarefas e canais de comunicação. Plataformas de integração são ferramentas para projetar e executar processos de integração, nas quais o motor de execução é o componente responsável pelo tempo de execução das tarefas e pela alocação de recursos computacionais que as executam. O processamento de um grande volume de dados, correspondendo a execução de milhões de tarefas, pode causar situações de sobrecarga, caracterizadas pelo acúmulo de tarefas em filas internas que aguardam recursos computacionais nos motores de execução, resultando em tempos de resposta inaceitáveis para aplicações e usuários externos. Nossa hipótese de pesquisa é que os motores de execução das plataformas de integração usam heurísticas simplistas para agendar tarefas, o que não lhes permitem manter níveis aceitáveis de desempenho em situações de sobrecarga. Neste trabalho de pesquisa, desenvolvemos (i) uma representação para processos de integração, (ii) uma caracterização para seus agendamentos de tarefas, (iii) uma heurística para lidar com situações de sobrecarga, (iv) um modelo matemático para uma métrica de desempenho da execução de processos de integração e (v) uma ferramenta de simulação para heurísticas de agendamento de tarefas. Nossos resultados de pesquisa indicam que, em situações de sobrecarga, nossa heurística promove uma distribuição equilibrada da carga de trabalho e um aumento no desempenho da execução dos processos de integração

The Virtual Manufacturing concept: Scope, Socio-Economic Aspects and Future Trends

International audienceThe research area "Virtual Manufacturing (VM)'' is the use of information technology and computer simulation to model real world manufacturing processes for the purpose of analysing and understanding them. As automation technologies such as CAD/CAM have substantially shortened the time required to design products, Virtual Manufacturing will have a similar effect on the manufacturing phase thanks to the modelling, simulation and optimisation of the product and the processes involved in its fabrication. After a description of Virtual Manufacturing (definitions and scope), we present some socio-economic factors of VM and finaly some "hot topics'' for the future are proposed

An SDS Modeling Approach for Simulation-Based Control

We initiate a study of mathematical models for specifying (discrete) simulation-based control systems. It is desirable to specify simulation-based control systems using a model that is intuitive, succinct, expressive, and whose state space properties are relatively easy computationally. We compare automata-based models for specifying control systems and find that all systems that are currently used (such as finite state machines, communicating hierarchical finite state machines (FSM), communicating finite state machines, and Turing machines) lack at least one of the abovementioned features. We propose using sequential dynamical systems (SDS) - a formalism for representing discrete simulations - to specify simulation-based control systems. We show how to adapt the standard SDS model to specify cell-level controllers for a generic cell. For reasonable flexible manufacturing cells, the SDS-based specification has size polynomial in the size of the cell, while in the worst case the FSM-based specification has size exponential in the size of the cell

An SDS Modeling Approach for Simulation-Based Control

We initiate a study of mathematical models for specifying (discrete) simulation-based control systems. It is desirable to specify simulation-based control systems using a model that is intuitive, succinct, expressive, and whose state space properties are relatively easy computationally. We compare automata-based models for specifying control systems and find that all systems that are currently used (such as finite state machines, communicating hierarchical finite state machines (FSM), communicating finite state machines, and Turing machines) lack at least one of the abovementioned features. We propose using sequential dynamical systems (SDS) - a formalism for representing discrete simulations - to specify simulation-based control systems. We show how to adapt the standard SDS model to specify cell-level controllers for a generic cell. For reasonable flexible manufacturing cells, the SDS-based specification has size polynomial in the size of the cell, while in the worst case the FSM-based specification has size exponential in the size of the cell