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This guide demonstrates how virtual build and test can be supported
by the Discrete Event Systems Specification (DEVS) simulation
modeling formalism, and the System Entity Structure (SES)
simulation model ontology. The book examines a wide variety of
Systems of Systems (SoS) problems, ranging from cloud computing
systems to biological systems in agricultural food crops. Features:
includes numerous exercises, examples and case studies throughout
the text; presents a step-by-step introduction to DEVS concepts,
encouraging hands-on practice to building sophisticated SoS models;
illustrates virtual build and test for a variety of SoS
applications using both commercial and open source DEVS simulation
environments; introduces an approach based on activity concepts
intrinsic to DEVS-based system design, that integrates both energy
and information processing requirements; describes co-design
modeling concepts and methods to capture separate and integrated
software and hardware systems.
During the 1990s the computing industry has witnessed many advances
in mobile and enterprise computing. Many of these advances have
been made possible by developments in the areas such as modeling,
simulation, and artificial intelligence. Within the different areas
of enterprise computing - such as manufacturing, health
organisation, and commerce - the need for a disciplined,
multifaceted, and unified approach to modeling and simulation has
become essential. This new book provides a forum for scientists,
academics, and professionals to present their latest research
findings from the various fields: artificial intelligence,
collaborative/distributed computing, modeling, and simulation.
The underlying technologies enabling the realization of recent advances in areas like mobile and enterprise computing are artificial intelligence (AI), modeling and simulation, and software engineering. A disciplined, multifaceted, and unified approach to modeling and simulation is now essential in new frontiers, such as Simulation Based Acquisition. This volume is an edited survey of international scientists, academicians, and professionals who present their latest research findings in the various fields of AI; collaborative/distributed computing; and modeling, simulation, and their integration. Whereas some of these areas continue to seek answers to basic fundamental scientific inquiries, new questions have emerged only recently due to advances in computing infrastructures, technologies, and tools. The book¿s principal goal is to provide a unifying forum for developing postmodern, AI-based modeling and simulation environments and their utilization in both traditional and modern application domains. Features and topics: * Blends comprehensive, advanced modeling and simulation theories and methodologies in a presentation founded on formal, system-theoretic and AI-based approaches * Uses detailed, real-world examples to illustrate key concepts in systems theory, modeling, simulation, object orientation, and intelligent systems * Addresses a broad range of critical topics in the areas of modeling frameworks, distributed and high-performance object-oriented simulation approaches, as well as robotics, learning, multi-scale and multi-resolution models, and multi-agent systems * Includes new results pertaining to intelligent and agent-based modeling, the relationship between AI-based reasoning and Discrete-Event System Specification, and large-scale distributed modeling and simulation frameworks * Provides cross-disciplinary insight into how computer science, computer engineering, and systems engineering can collectively provide a rich set of theories and methods enabling contemporary modeling and simulation This state-of-the-art survey on collaborative/distributed modeling and simulation computing environments is an essential resource for the latest developments and tools in the field for all computer scientists, systems engineers, and software engineers. Professionals, practitioners, and graduate students will find this reference invaluable to their work involving computer simulation, distributed modeling, discrete-event systems, AI, and software engineering.
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