Cooperative and Distributed Intelligent Computation in Fog Computing

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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.

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.

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Hoa Tran-Dang

Themen in »Cooperative and Distributed Intelligent Computation in Fog Computing«

Fog computing Edge computing IoT Distributed and Parallel Computation Task Partition Reinforcement Learning Resource Allocation Resource Management Task Offloading Full offloading Partial Offloading Matching Theory Bandit Learning

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