List of requirements on formalisms and selection of appropriate tools

This deliverable reports on the activities for the set-up of the modelling environments for the evaluation activities of WP5. To this objective, it reports on the identified modelling peculiarities of the electric power infrastructure and the information infrastructures and of their interdependencies, recalls the tools that have been considered and concentrates on the tools that are, and will be, used in the project: DrawNET, DEEM and EPSys which have been developed before and during the project by the partners, and M\uf6bius and PRISM, developed respectively at the University of Illinois at Urbana Champaign and at the University of Birmingham (and recently at the University of Oxford)

Formalizing Cyber--Physical System Model Transformation via Abstract Interpretation

Model transformation tools assist system designers by reducing the labor--intensive task of creating and updating models of various aspects of systems, ensuring that modeling assumptions remain consistent across every model of a system, and identifying constraints on system design imposed by these modeling assumptions. We have proposed a model transformation approach based on abstract interpretation, a static program analysis technique. Abstract interpretation allows us to define transformations that are provably correct and specific. This work develops the foundations of this approach to model transformation. We define model transformation in terms of abstract interpretation and prove the soundness of our approach. Furthermore, we develop formalisms useful for encoding model properties. This work provides a methodology for relating models of different aspects of a system and for applying modeling techniques from one system domain, such as smart power grids, to other domains, such as water distribution networks.Comment: 8 pages, 4 figures; to appear in HASE 2019 proceeding

Proceedings of the 4th Workshop of the MPM4CPS COST Action

Proceedings of the 4th Workshop of the MPM4CPS COST Action with the presentations delivered during the workshop and papers with extended versions of some of them

High-Performance Modelling and Simulation for Big Data Applications

This open access book was prepared as a Final Publication of the COST Action IC1406 “High-Performance Modelling and Simulation for Big Data Applications (cHiPSet)“ project. Long considered important pillars of the scientific method, Modelling and Simulation have evolved from traditional discrete numerical methods to complex data-intensive continuous analytical optimisations. Resolution, scale, and accuracy have become essential to predict and analyse natural and complex systems in science and engineering. When their level of abstraction raises to have a better discernment of the domain at hand, their representation gets increasingly demanding for computational and data resources. On the other hand, High Performance Computing typically entails the effective use of parallel and distributed processing units coupled with efficient storage, communication and visualisation systems to underpin complex data-intensive applications in distinct scientific and technical domains. It is then arguably required to have a seamless interaction of High Performance Computing with Modelling and Simulation in order to store, compute, analyse, and visualise large data sets in science and engineering. Funded by the European Commission, cHiPSet has provided a dynamic trans-European forum for their members and distinguished guests to openly discuss novel perspectives and topics of interests for these two communities. This cHiPSet compendium presents a set of selected case studies related to healthcare, biological data, computational advertising, multimedia, finance, bioinformatics, and telecommunications

High-Performance Modelling and Simulation for Big Data Applications

This open access book was prepared as a Final Publication of the COST Action IC1406 “High-Performance Modelling and Simulation for Big Data Applications (cHiPSet)“ project. Long considered important pillars of the scientific method, Modelling and Simulation have evolved from traditional discrete numerical methods to complex data-intensive continuous analytical optimisations. Resolution, scale, and accuracy have become essential to predict and analyse natural and complex systems in science and engineering. When their level of abstraction raises to have a better discernment of the domain at hand, their representation gets increasingly demanding for computational and data resources. On the other hand, High Performance Computing typically entails the effective use of parallel and distributed processing units coupled with efficient storage, communication and visualisation systems to underpin complex data-intensive applications in distinct scientific and technical domains. It is then arguably required to have a seamless interaction of High Performance Computing with Modelling and Simulation in order to store, compute, analyse, and visualise large data sets in science and engineering. Funded by the European Commission, cHiPSet has provided a dynamic trans-European forum for their members and distinguished guests to openly discuss novel perspectives and topics of interests for these two communities. This cHiPSet compendium presents a set of selected case studies related to healthcare, biological data, computational advertising, multimedia, finance, bioinformatics, and telecommunications

Decisión making and decisión support systems for balancing Socio-Economic and Natural Capital Development.

The paper discusses briefly a hierarchical spatio-temporal framework to study globalization, economics and ecology for better understanding and conceptualization of the balance between biodiversity and Natural Capital (NC) on one side, and the Socio-Economic Systems (SES), on the other side, which was designed based on the recent achievements in the field of Systems Ecology. Based on the conceptual clarification of the dynamic condictions for sustainability and on an extensive review of the most recent literature, there are proposed and discussed the decision support system and decision making model as the operational interface between Natural Capital components and Socio-Economic Systems, which might enable to establish and maintain the balance among them. The identified weaknesses and gaps in the structure and function of the Decision Support System (DSS) show the need for extensive and long term research and integrated monitoring and for development and improvement of the methodology and tools.Sin resume

Demystifying Usability of Open Source Computational Offloading Simulators : Performance Evaluation Campaign

Along with analysis and practical implementation, simulations play a key role in wireless networks and computational offloading research for several reasons. First, the simulations provide the ability to easily obtain the data for a complex system’s model evaluation. Secondly, simulated data provides a controlled environment for experimentation, allowing models and algorithms to be tested for robustness and identifying potential limitations before deploying them in real-world applications. Choosing the most appropriate tool for simulation might be challenging and depends on several factors, such as the main purpose, complexity of data, researcher skills, community support, and available budget. As of the time of the present analysis, several system-level open-source tools for modeling computational offloading also cover the systems’ communications side, such as CloudSim , CloudSim Plus , IoTSim-Edge , EdgeCloudSim , iFogSim2 , PureEdgeSim , and YAFS . This work presents an evaluation of those based on the unique features and performance results of intensive workload- and delay-tolerant scenarios: XR with an extremely high data rate and workload; remote monitoring with a low data rate with moderate delays and workload requirements; and data streaming as a general human traffic with a relatively high bit rate but moderate workload. The work concludes that CloudSim provides a reliable environment for virtualization on the host resources, while YAFS shows minimal hardware usage, while IoTSim-Edge , PureEdgeSim , and EdgeCloudSim have fewer implemented features.Peer reviewe

Discrete-Event Simulation Data Transformation: A Model-Driven Data Integration Approach

Achieving a smooth production system is a complex process that requires the use of commercial discrete event simulation (DES) tools to provide a high flexibility production process, for instance the use of simulation modelling to model a production system. These tools require high levels of cooperation to work together because they are not designed to be integrated and hardly share their data. This research aims to integrate DES tools applied by different manufacturing systems in order to enable them to share their data. This thesis presents data integration from a simulation model point of view because it views data integration between different DES tools models as key steps towards system integration. A new approach has been developed which is called a Model-Driven Data Integration Approach (MDDI), so named because the integration involves the combination of data from different DES tools model sources. The effectiveness of this data integration approach has been demonstrated in a case study undertaken for DES design of a phone production line in the manufacturing industry. However, the application of the MDDI is not limited to this case study: it can also be used for other system and applications. The MDDI approach was tested and evaluated on the basis of this case study. These test cases simulated how the data integration based on different DES tools’ models react to the process of data sharing as they occur in the manufacturing production line. The result is that the MDDI approach best maintains data consistency and integrity and can be adopted by different industries