Machine learning meets computation and communication control in evolving edge and cloud: Challenges and future perspective
Mobile Edge Computing (MEC) is considered an essential future service for the
implementation of 5G networks and the Internet of Things, as it is the best method of …
implementation of 5G networks and the Internet of Things, as it is the best method of …
Blockchain empowered asynchronous federated learning for secure data sharing in internet of vehicles
In Internet of Vehicles (IoV), data sharing among vehicles for collaborative analysis can
improve the driving experience and service quality. However, the bandwidth, security and …
improve the driving experience and service quality. However, the bandwidth, security and …
Energy-efficient UAV-assisted mobile edge computing: Resource allocation and trajectory optimization
In this paper, we study unmanned aerial vehicle (UAV) assisted mobile edge computing
(MEC) with the objective to optimize computation offloading with minimum UAV energy …
(MEC) with the objective to optimize computation offloading with minimum UAV energy …
Task offloading in vehicular edge computing networks: A load-balancing solution
Recently, the rapid advance of vehicular networks has led to the emergence of diverse delay-
sensitive vehicular applications such as automatic driving, auto navigation. Note that …
sensitive vehicular applications such as automatic driving, auto navigation. Note that …
[HTML][HTML] A survey of federated learning for edge computing: Research problems and solutions
Federated Learning is a machine learning scheme in which a shared prediction model can
be collaboratively learned by a number of distributed nodes using their locally stored data. It …
be collaboratively learned by a number of distributed nodes using their locally stored data. It …
Blockchain-based on-demand computing resource trading in IoV-assisted smart city
In a smart city, Mobile Edge Computing (MEC) are generally deployed in static fashion in
base stations (BSs). While moving vehicles with advanced on-board equipment can be …
base stations (BSs). While moving vehicles with advanced on-board equipment can be …
Reducing offloading latency for digital twin edge networks in 6G
W Sun, H Zhang, R Wang… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
6G is envisioned to empower wireless communication and computation through the
digitalization and connectivity of everything, by establishing a digital representation of the …
digitalization and connectivity of everything, by establishing a digital representation of the …
Deep reinforcement learning and permissioned blockchain for content caching in vehicular edge computing and networks
Vehicular Edge Computing (VEC) is a promising paradigm to enable huge amount of data
and multimedia content to be cached in proximity to vehicles. However, high mobility of …
and multimedia content to be cached in proximity to vehicles. However, high mobility of …
Partial offloading scheduling and power allocation for mobile edge computing systems
Mobile edge computing (MEC) is a promising technique to enhance computation capacity at
the edge of mobile networks. The joint problem of partial offloading decision, offloading …
the edge of mobile networks. The joint problem of partial offloading decision, offloading …
Latency minimization for D2D-enabled partial computation offloading in mobile edge computing
We consider Device-to-Device (D2D)-enabled mobile edge computing offloading scenario,
where a device can partially offload its computation task to the edge server or exploit the …
where a device can partially offload its computation task to the edge server or exploit the …