The growing awareness of the effects that simulation is having on the way we design our computing, communication, and control systems is leading to an increased demand for a better understanding of all aspects of simulation, ANSS'03 covers broad topics in the areas of distributed systems, network modeling, and advances in simulation methodology and practices.
Large-Scale Simulation: Models, Algorithms, and Applications gives you firsthand insight on the latest advances in large-scale simulation techniques. Most of the research results are drawn from the authors’ papers in top-tier, peer-reviewed, scientific conference proceedings and journals. The first part of the book presents the fundamentals of large-scale simulation, including high-level architecture and runtime infrastructure. The second part covers middleware and software architecture for large-scale simulations, such as decoupled federate architecture, fault tolerant mechanisms, grid-enabled simulation, and federation communities. In the third part, the authors explore mechanisms—such as simulation cloning methods and algorithms—that support quick evaluation of alternative scenarios. The final part describes how distributed computing technologies and many-core architecture are used to study social phenomena. Reflecting the latest research in the field, this book guides you in using and further researching advanced models and algorithms for large-scale distributed simulation. These simulation tools will help you gain insight into large-scale systems across many disciplines.
Collecting the work of the foremost scientists in the field, Discrete-Event Modeling and Simulation: Theory and Applications presents the state of the art in modeling discrete-event systems using the discrete-event system specification (DEVS) approach. It introduces the latest advances, recent extensions of formal techniques, and real-world examples of various applications. The book covers many topics that pertain to several layers of the modeling and simulation architecture. It discusses DEVS model development support and the interaction of DEVS with other methodologies. It describes different forms of simulation supported by DEVS, the use of real-time DEVS simulation, the relationship between DEVS and graph transformation, the influence of DEVS variants on simulation performance, and interoperability and composability with emphasis on DEVS standardization. The text also examines extensions to DEVS, new formalisms, and abstractions of DEVS models as well as the theory and analysis behind real-world system identification and control. To support the generation and search of optimal models of a system, a framework is developed based on the system entity structure and its transformation to DEVS simulation models. In addition, the book explores numerous interesting examples that illustrate the use of DEVS to build successful applications, including optical network-on-chip, construction/building design, process control, workflow systems, and environmental models. A one-stop resource on advances in DEVS theory, applications, and methodology, this volume offers a sampling of the best research in the area, a broad picture of the DEVS landscape, and trend-setting applications enabled by the DEVS approach. It provides the basis for future research discoveries and encourages the development of new applications.
Security-enriched urban computing and smart grids are areas that attracted many a- demic and industry professionals to research and develop. The goal of this conference was to bring together researchers from academia and industry as well as practitioners to share ideas, problems and solutions relating to the multifaceted aspects of urban computing and the smart grid. This conference includes the following special sessions: Signal Processing, Image Processing, Pattern Recognition and Communications (SIPC 2010), Networking, Fault-tolerance and Security For Distributed Computing Systems (NFSDCS 2010), Security Technology Application (STA 2010), Electric Transportation (ElecTrans 2010), Techniques of Bi-directional Power Computing in High Voltage Power Supply (TBPC 2010), Low Power IT and Applications (LPITA 2010), Computational Intel- gence and Soft Computing (CISC 2010), Distributed Computing and Sensor Networks (DCSN 2010), Advanced Fusion IT (AFIT 2010), Social Media and Social Netwo- ing (SMSN 2010), Software Engineering and Medical Information Engineering (SEMIE 2010), Human-Centered Advanced Research/Education (HuCARE 2010), Database Integrity and Security (DIS 2010), Ubiquitous IT Application (UITA 2010) and Smart Grid Applications (SGA 2010). We would like to express our gratitude to all of the authors of the submitted papers and to all attendees, for their contributions and participation. We believe in the need for continuing this undertaking in the future.
Web caching and content delivery technologies provide the infrastructure on which systems are built for the scalable distribution of information. This proceedings of the eighth annual workshop, captures a cross-section of the latest issues and techniques of interest to network architects and researchers in large-scale content delivery. Topics covered include the distribution of streaming multimedia, edge caching and computation, multicast, delivery of dynamic content, enterprise content delivery, streaming proxies and servers, content transcoding, replication and caching strategies, peer-to-peer content delivery, and Web prefetching. Web Content Caching and Distribution encompasses all areas relating to the intersection of storage and networking for Internet content services. The book is divided into eight parts: mobility, applications, architectures, multimedia, customization, peer-to-peer, performance and measurement, and delta encoding.
This volume constitutes the refereed proceedings of the Third International Conference on Contemporary Computing, IC3 2010, held in Noida, India, in August 2010.
Integrating Intelligence and Sustainability in Supply Chains is a comprehensive research guide that delves into the realm of sustainable and smart supply chains. With a focus on bridging the gap between intelligence and sustainability, this book provides a valuable resource for graduate students in business, management, industrial engineering, and industrial ecology. It serves as a unifying platform for researchers across various domains, including operations management, industrial ecology, industrial strategy, risk management, and life cycle assessment, who are passionate about sustainable and smart supply chains. This book offers a wealth of groundbreaking insights from renowned scholars and field experts. It serves as a theoretical and conceptual foundation for environmental researchers seeking a business, policy, or industry perspective. By addressing the key issues at the intersection of operations management and environmental and social responsibility, the book presents a novel approach to mitigating negative impacts and aligning logistics with sustainability and digitalization requirements. Structured in a modular format, this book allows readers to explore specific current topics relevant to their interests. It covers a wide range of subjects, such as measuring environmental impacts, transforming supply chains to meet sustainability challenges, business models for sustainable logistics, and integrative business strategies. Furthermore, the book addresses emerging technologies like big data analytics, artificial intelligence, and the Internet of Things (IoT), exploring their applications in supply chain management.
The book aims to outline the issues of AI and COVID-19, involving predictions,medical support decision-making, and possible impact on human life. Starting withmajor COVID-19 issues and challenges, it takes possible AI-based solutions forseveral problems, such as public health surveillance, early (epidemic) prediction,COVID-19 positive case detection, and robotics integration against COVID-19.Beside mathematical modeling, it includes the necessity of changes in innovationsand possible COVID-19 impacts. The book covers a clear understanding of AI-driven tools and techniques, where pattern recognition, anomaly detection, machinelearning, and data analytics are considered. It aims to include the wide range ofaudiences from computer science and engineering to healthcare professionals.
