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X-Machines for Agent-Based Modeling
From the Foreword: "This book exemplifies one of the most successful approaches to modeling and simulating [the] new generation of complex systems. FLAME was designed to make the building of large scale complex systems models straightforward and the simulation code that it generates is highly efficient and can be run on any modern technology. FLAME was the first such platform that ran efficiently on high performance parallel computers and a version for GPU technology is also available. At its heart, and the reason why it is so efficient and robust, is the use of a powerful computational model ‘Communicating X-machines’ which is general enough to cope with most types of modelling problems...
Online Banking Security Measures and Data Protection
Technological innovations in the banking sector have provided numerous benefits to customers and banks alike; however, the use of e-banking increases vulnerability to system attacks and threats, making effective security measures more vital than ever. Online Banking Security Measures and Data Protection is an authoritative reference source for the latest scholarly material on the challenges presented by the implementation of e-banking in contemporary financial systems. Presenting emerging techniques to secure these systems against potential threats and highlighting theoretical foundations and real-world case studies, this book is ideally designed for professionals, practitioners, upper-level students, and technology developers interested in the latest developments in e-banking security.
Modeling and Simulation of Complex Systems
Robert Siegfried presents a framework for efficient agent-based modeling and simulation of complex systems. He compares different approaches for describing structure and dynamics of agent-based models in detail. Based on this evaluation the author introduces the “General Reference Model for Agent-based Modeling and Simulation” (GRAMS). Furthermore he presents parallel and distributed simulation approaches for execution of agent-based models –from small scale to very large scale. The author shows how agent-based models may be executed by different simulation engines that utilize underlying hardware resources in an optimized fashion.
Machine Learning for Networking
This book constitutes the thoroughly refereed proceedings of the Second International Conference on Machine Learning for Networking, MLN 2019, held in Paris, France, in December 2019. The 26 revised full papers included in the volume were carefully reviewed and selected from 75 submissions. They present and discuss new trends in deep and reinforcement learning, pattern recognition and classification for networks, machine learning for network slicing optimization, 5G system, user behavior prediction, multimedia, IoT, security and protection, optimization and new innovative machine learning methods, performance analysis of machine learning algorithms, experimental evaluations of machine learning, data mining in heterogeneous networks, distributed and decentralized machine learning algorithms, intelligent cloud-support communications, ressource allocation, energy-aware communications, software de ned networks, cooperative networks, positioning and navigation systems, wireless communications, wireless sensor networks, underwater sensor networks.
Artificial Intelligence For Science: A Deep Learning Revolution
This unique collection introduces AI, Machine Learning (ML), and deep neural network technologies leading to scientific discovery from the datasets generated both by supercomputer simulation and by modern experimental facilities.Huge quantities of experimental data come from many sources — telescopes, satellites, gene sequencers, accelerators, and electron microscopes, including international facilities such as the Large Hadron Collider (LHC) at CERN in Geneva and the ITER Tokamak in France. These sources generate many petabytes moving to exabytes of data per year. Extracting scientific insights from these data is a major challenge for scientists, for whom the latest AI developments will be essential.The timely handbook benefits professionals, researchers, academics, and students in all fields of science and engineering as well as AI, ML, and neural networks. Further, the vision evident in this book inspires all those who influence or are influenced by scientific progress.
High Performance Computing
This book constitutes the refereed proceedings of the 37th International Conference on High Performance Computing, ISC High Performance 2022, held in Hamburg, Germany, during May 29 – June 2, 2022. The 18 full papers presented were carefully reviewed and selected from 53 submissions. The papers are categorized into the following topical sub-headings: Architecture, Networks, and Storage; Machine Learning, AI, Emerging Technologies; HPC Algorithms and Applications; Performance Modeling, Evaluation and Analysis; and Programming Environments and Systems Software.
Cloud Computing
This book reviews the challenging issues that present barriers to greater implementation of the cloud computing paradigm, together with the latest research into developing potential solutions. Topics and features: presents a focus on the most important issues and limitations of cloud computing, covering cloud security and architecture, QoS and SLAs; discusses a methodology for cloud security management, and proposes a framework for secure data storage and identity management in the cloud; introduces a simulation tool for energy-aware cloud environments, and an efficient congestion control system for data center networks; examines the issues of energy-aware VM consolidation in the IaaS provision, and software-defined networking for cloud related applications; reviews current trends and suggests future developments in virtualization, cloud security, QoS data warehouses, cloud federation approaches, and DBaaS provision; predicts how the next generation of utility computing infrastructures will be designed.
Advances in Service-Oriented and Cloud Computing
This volume contains the technical papers presented in the four high-quality workshops associated with the European Conference on Service-Oriented and Cloud Computing, ESOCC 2014, held in Manchester, UK, in September 2014: 4th International Workshop on Adaptive Services for the Future Internet, WAS4FI 2014, 2nd International Workshop on Cloud for IoT, CLIoT 2014, 2nd International Workshop on Cloud Service Brokerage, CSB 2014, and Seamless Adaptive Multi-cloud Management of Service-based Applications, SeaCloudS Workshop. The 19 revised full papers and 3 short papers were carefully reviewed and selected from 39 submissions. They focus on specific topics in service-oriented and cloud computing domains as cloud computing, service buses, Web services, service-oriented architectures, event-driven architectures, enterprise architectures, business process management, software selection and adaptation.
Machine Learning for Networking
This book constitutes the thoroughly refereed proceedings of the Second International Conference on Machine Learning for Networking, MLN 2019, held in Paris, France, in December 2019. The 26 revised full papers included in the volume were carefully reviewed and selected from 75 submissions. They present and discuss new trends in deep and reinforcement learning, patternrecognition and classi cation for networks, machine learning for network slicingoptimization, 5G system, user behavior prediction, multimedia, IoT, securityand protection, optimization and new innovative machine learning methods, performanceanalysis of machine learning algorithms, experimental evaluations ofmachine learning, data mining in heterogeneous networks, distributed and decentralizedmachine learning algorithms, intelligent cloud-support communications,ressource allocation, energy-aware communications, software de ned networks,cooperative networks, positioning and navigation systems, wireless communications,wireless sensor networks, underwater sensor networks.
Cloud Security: Concepts, Methodologies, Tools, and Applications
Cloud computing has experienced explosive growth and is expected to continue to rise in popularity as new services and applications become available. As with any new technology, security issues continue to be a concern, and developing effective methods to protect sensitive information and data on the cloud is imperative. Cloud Security: Concepts, Methodologies, Tools, and Applications explores the difficulties and challenges of securing user data and information on cloud platforms. It also examines the current approaches to cloud-based technologies and assesses the possibilities for future advancements in this field. Highlighting a range of topics such as cloud forensics, information privacy, and standardization and security in the cloud, this multi-volume book is ideally designed for IT specialists, web designers, computer engineers, software developers, academicians, researchers, and graduate-level students interested in cloud computing concepts and security.
