In areas such as military, security, aerospace, and disaster management, the need for performance optimization and interoperability among heterogeneous systems is increasingly important. Model-driven engineering, a paradigm in which the model becomes the actual software, offers a promising approach toward systems of systems (SoS) engineering. However, model-driven engineering has largely been unachieved in complex dynamical systems and netcentric SoS, partly because modeling and simulation (M&S) frameworks are stove-piped and not designed for SoS composability. Addressing this gap, Netcentric System of Systems Engineering with DEVS Unified Process presents a methodology for realizing the model-driven engineering vision and netcentric SoS using DEVS Unified Process (DUNIP). The authors draw on their experience with Discrete Event Systems Specification (DEVS) formalism, System Entity Structure (SES) theory, and applying model-driven engineering in the context of a netcentric SoS. They describe formal model-driven engineering methods for netcentric M&S using standards-based approaches to develop and test complex dynamic models with DUNIP. The book is organized into five sections: Section I introduces undergraduate students and novices to the world of DEVS. It covers systems and SoS M&S as well as DEVS formalism, software, modeling language, and DUNIP. It also assesses DUNIP with the requirements of the Department of Defense's (DoD) Open Unified Technical Framework (OpenUTF) for netcentric Test and Evaluation (T&E). Section II delves into M&S-based systems engineering for graduate students, advanced practitioners, and industry professionals. It provides methodologies to apply M&S principles to SoS design and reviews the development of executable architectures based on a framework such as the Department of Defense Architecture Framework (DoDAF). It also describes an approach for building netcentric knowledge-based contingency-driven systems. Section III guides graduate students, advanced DEVS users, and industry professionals who are interested in building DEVS virtual machines and netcentric SoS. It discusses modeling standardization, the deployment of models and simulators in a netcentric environment, event-driven architectures, and more. Section IV explores real-world case studies that realize many of the concepts defined in the previous chapters. Section V outlines the next steps and looks at how the modeling of netcentric complex adaptive systems can be attempted using DEVS concepts. It touches on the boundaries of DEVS formalism and the future work needed to utilize advanced concepts like weak and strong emergence, self-organization, scale-free systems, run-time modularity, and event interoperability. This groundbreaking work details how DUNIP offers a well-structured, platform-independent methodology for the modeling and simulation of netcentric system of systems.

In areas such as military, security, aerospace, and disaster management, the need for performance optimization and interoperability among heterogeneous systems is increasingly important. Model-driven engineering, a paradigm in which the model becomes the actual software, offers a promising approach toward systems of systems (SoS) engineering. However, model-driven engineering has largely been unachieved in complex dynamical systems and netcentric SoS, partly because modeling and simulation (M&S) frameworks are stove-piped and not designed for SoS composability. Addressing this gap, Netcentric System of Systems Engineering with DEVS Unified Process presents a methodology for realizing the model-driven engineering vision and netcentric SoS using DEVS Unified Process (DUNIP). The authors draw on their experience with Discrete Event Systems Specification (DEVS) formalism, System Entity Structure (SES) theory, and applying model-driven engineering in the context of a netcentric SoS. They describe formal model-driven engineering methods for netcentric M&S using standards-based approaches to develop and test complex dynamic models with DUNIP. The book is organized into five sections: Section I introduces undergraduate students and novices to the world of DEVS. It covers systems and SoS M&S as well as DEVS formalism, software, modeling language, and DUNIP. It also assesses DUNIP with the requirements of the Department of Defense's (DoD) Open Unified Technical Framework (OpenUTF) for netcentric Test and Evaluation (T&E). Section II delves into M&S-based systems engineering for graduate students, advanced practitioners, and industry professionals. It provides methodologies to apply M&S principles to SoS design and reviews the development of executable architectures based on a framework such as the Department of Defense Architecture Framework (DoDAF). It also describes an approach for building netcentric knowledge-based contingency-driven systems. Section III guides graduate students, advanced DEVS users, and industry professionals who are interested in building DEVS virtual machines and netcentric SoS. It discusses modeling standardization, the deployment of models and simulators in a netcentric environment, event-driven architectures, and more. Section IV explores real-world case studies that realize many of the concepts defined in the previous chapters. Section V outlines the next steps and looks at how the modeling of netcentric complex adaptive systems can be attempted using DEVS concepts. It touches on the boundaries of DEVS formalism and the future work needed to utilize advanced concepts like weak and strong emergence, self-organization, scale-free systems, run-time modularity, and event interoperability. This groundbreaking work details how DUNIP offers a well-structured, platform-independent methodology for the modeling and simulation of netcentric system of systems.

This comprehensive book examines a range of examples, prepared by a diverse group of academic and industry practitioners, which demonstrate how cloud-based simulation is being extensively used across many disciplines, including cyber-physical systems engineering. This book is a compendium of the state of the art in cloud-based simulation that instructors can use to inform the next generation. It highlights the underlying infrastructure, modeling paradigms, and simulation methodologies that can be brought to bear to develop the next generation of systems for a highly connected society. Such systems, aptly termed cyber-physical systems (CPS), are now widely used in e.g. transportation systems, smart grids, connected vehicles, industrial production systems, healthcare, education, and defense. Modeling and simulation (M&S), along with big data technologies, are at the forefront of complex systems engineering research. The disciplines of cloud-based simulation and CPS engineering are evolving at a rapid pace, but are not optimally supporting each other's advancement. This book brings together these two communities, which already serve multi-disciplinary applications. It provides an overview of the simulation technologies landscape, and of infrastructure pertaining to the use of cloud-based environments for CPS engineering. It covers the engineering, design, and application of cloud simulation technologies and infrastructures applicable for CPS engineering. The contributions share valuable lessons learned from developing real-time embedded and robotic systems deployed through cloud-based infrastructures for application in CPS engineering and IoT-enabled society. The coverage incorporates cloud-based M&S as a medium for facilitating CPS engineering and governance, and elaborates on available cloud-based M&S technologies and their impacts on specific aspects of CPS engineering.

This comprehensive book examines a range of examples, prepared by a diverse group of academic and industry practitioners, which demonstrate how cloud-based simulation is being extensively used across many disciplines, including cyber-physical systems engineering. This book is a compendium of the state of the art in cloud-based simulation that instructors can use to inform the next generation. It highlights the underlying infrastructure, modeling paradigms, and simulation methodologies that can be brought to bear to develop the next generation of systems for a highly connected society. Such systems, aptly termed cyber-physical systems (CPS), are now widely used in e.g. transportation systems, smart grids, connected vehicles, industrial production systems, healthcare, education, and defense. Modeling and simulation (M&S), along with big data technologies, are at the forefront of complex systems engineering research. The disciplines of cloud-based simulation and CPS engineering are evolving at a rapid pace, but are not optimally supporting each other's advancement. This book brings together these two communities, which already serve multi-disciplinary applications. It provides an overview of the simulation technologies landscape, and of infrastructure pertaining to the use of cloud-based environments for CPS engineering. It covers the engineering, design, and application of cloud simulation technologies and infrastructures applicable for CPS engineering. The contributions share valuable lessons learned from developing real-time embedded and robotic systems deployed through cloud-based infrastructures for application in CPS engineering and IoT-enabled society. The coverage incorporates cloud-based M&S as a medium for facilitating CPS engineering and governance, and elaborates on available cloud-based M&S technologies and their impacts on specific aspects of CPS engineering.

The book provides a layout of how caching can be used for effective communication in case of wireless networks. Also a new algorithm was derived to provide the solution of packet loss in case of any one weak sensor node over the network. Detect the weak sensor node over the network and then block it or set its load to the minimum. Instead of transferring data on this node, it will be pass on from the surrounding nodes. Performed the delay analysis by comparing the throughput with the Expected output and in this case data transmission is secure. The algorithm will provide the better solution for minimum packet loss.