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Advanced Deep Learning for Resource Allocation and Security Aware Data Offloading in Industrial Mobile Edge Computing bandwidth utilization lead to the shift from mobile cloud computing to mobile edge computing. In this study

Hierarchical data fusion for Smart Healthcare in the context of IoT networks, consisting of edge devices, network and communications units, and Cloud platforms

Improving performance and data transmission security in VANETs of the vehicular network. The proposed approach is the combination of 5G cellular network and alternative data

Exploiting D2D communications at the network edge for mission-critical IoT applications are to be met. A viable way of development is the integration of local clouds at the edge of the network as part

Dd-fog: Intelligent distributed dynamic fog computing framework of new services with new cloud computing structures such as fog and edge. In spite of this, the complex

Data Processing in Cyber-Physical-Social Systems Through Edge Computing© 2013 IEEE. Cloud and Fog computing have established a convenient and widely adopted approach

Cloud computing in educationCloud computing in education

Peer Offloading with Delayed Feedback in Fog NetworksComparing to cloud computing, fog computing performs computation and services at the edge

Ray-Based Modeling of Unlicensed-Band mmWave Propagation Inside a City BusIntra-vehicular

IoT-fog based system structure with SDN enabledT devices and the remote cloud becomes a demand to make use of the edge computing benefits. In this work, we

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