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Cooperative and Distributed Intelligent Computation in Fog Computing: Concepts, Architectures, and FrameworksНазвание: Cooperative and Distributed Intelligent Computation in Fog Computing: Concepts, Architectures, and Frameworks
Автор: Hoa Tran-Dang, Dong-Seong Kim
Издательство: Springer
Год: 2023
Страниц: 211
Язык: английский
Формат: pdf (true), epub
Размер: 21.1 MB

This informative text/reference presents a detailed review of the state of the art in fog computing paradigm. In particular, the book examines a broad range of important cooperative and distributed computation algorithms, along with their design objectives and technical challenges.

The coverage includes the conceptual fundamental of fog computing, its practical applications, cooperative and distributed computation algorithms using optimization, swarm intelligence, matching theory, and reinforcement learning methods. Discussions are also provided on remaining challenges and open research issues for designing and developing the efficient distributed computation solutions in the next-generation of fog-enabled IoT systems.

The Internet of Things (IoT) paradigm has been expanded rapidly as a key pillar to realize the smart concept in various domains such as smart cities, smart grids, and smart factories since it enables the interconnection and interoperability of IoT-enabled physical and virtual entities to create smart services and informed decision-making for monitoring, control, and management purposes. The underlying principle of realization involves a set of activities that includes collecting, processing, analyzing, and getting insights from IoT data generated constantly by the IoT devices. Traditionally, the cloud computing platform plays an essential role in the realization process since it provides rich and powerful resources in terms of storage, computation, networking to handle an enormous amount of IoT data (big data) efficiently. However, more stringent requirements of IoT service provisioning such as (ultra)low delay expose crucial limitations of the cloud-based solutions because the delivery of data from the IoT devices to the centralized cloud computing servers seriously affects the performance in processing, analyzing data and results in network congestion issues and excessive delay as an ultimate consequence. This fact context leads to a strong push of fog computing integration into the IoT-cloud systems since it puts computing, storage, communication, and control closer to the IoT devices to meet the prescribed QoS requirements. Technically, the fog computing platform that is placed between the physical IoT devices and the cloud servers can handle a majority of service requests on behalf of the cloud servers to improve the system performance in terms of service delay, workload balancing, and resource utilization.

This book firstly provides an overview of innovative concepts of fog computing, and then proposes important methodologies to develop frameworks for performing intelligent distributed computation operations in the fog-enabled IoT systems. Concretely, the book discusses topics such as the basics of fog computing to help readers understand the technology from the ground up, details about the infrastructure and the integration of IoT, fog and cloud computing to help readers in gaining deeper insights into the technology. The book also includes the use of intelligent and optimal algorithms and emerging technologies like swarm intelligence and reinforcement learning with fog computing. Fundamentally, this book will be a readily accessible source of information for researchers in the area of distributed computing as well as for professionals who want to enhance their security and connectivity knowledge in IoT systems.

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