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A survey on the computation offloading approaches in mobile edge computing: A machine learning-based perspective
With the rapid developments in emerging mobile technologies, utilizing resource-hungry
mobile applications such as media processing, online Gaming, Augmented Reality (AR) …
mobile applications such as media processing, online Gaming, Augmented Reality (AR) …
Scheduling IoT applications in edge and fog computing environments: a taxonomy and future directions
Fog computing, as a distributed paradigm, offers cloud-like services at the edge of the
network with low latency and high-access bandwidth to support a diverse range of IoT …
network with low latency and high-access bandwidth to support a diverse range of IoT …
An application placement technique for concurrent IoT applications in edge and fog computing environments
Fog/Edge computing emerges as a novel computing paradigm that harnesses resources in
the proximity of the Internet of Things (IoT) devices so that, alongside with the cloud servers …
the proximity of the Internet of Things (IoT) devices so that, alongside with the cloud servers …
Secure and optimized load balancing for multitier IoT and edge-cloud computing systems
Mobile-edge computing (MEC) has emerged as a new computing paradigm with great
potential to alleviate resource limitations attributed to mobile device users (MDUs) by …
potential to alleviate resource limitations attributed to mobile device users (MDUs) by …
Efficient and secure multi-user multi-task computation offloading for mobile-edge computing in mobile IoT networks
Mobile edge computing (MEC) is a new paradigm to alleviate resource limitations of mobile
IoT networks through computation offloading with low latency. This article presents an …
IoT networks through computation offloading with low latency. This article presents an …
Data augmentation for deep learning-based radio modulation classification
Deep learning has recently been applied to automatically classify the modulation categories
of received radio signals without manual experience. However, training deep learning …
of received radio signals without manual experience. However, training deep learning …
Advanced deep learning-based computational offloading for multilevel vehicular edge-cloud computing networks
The promise of low latency connectivity and efficient bandwidth utilization has driven the
recent shift from vehicular cloud computing (VCC) towards vehicular edge computing (VEC) …
recent shift from vehicular cloud computing (VCC) towards vehicular edge computing (VEC) …
Intelligent computation offloading and resource allocation in IIoT with end-edge-cloud computing using NSGA-III
Industrial Internet of Things (IIoT), which consists of massive IoT devices and industrial
infrastructures such as wireless access points to acquire intelligent services, has been …
infrastructures such as wireless access points to acquire intelligent services, has been …
Meeting the requirements of internet of things: The promise of edge computing
Over the last few decades, Internet of Things (IoT) has become the spotlight area of research
within the Industries and Academics. Primarily, IoT devices are characterized by small and …
within the Industries and Academics. Primarily, IoT devices are characterized by small and …
Intelligent resource allocation for edge-cloud collaborative networks: A hybrid DDPG-D3QN approach
To handle the ever-increasing IoT devices with computation-intensive and delay-critical
applications, it is imperative to leverage the collaborative potential of edge and cloud …
applications, it is imperative to leverage the collaborative potential of edge and cloud …