For the goals of beyond 5G and 6G networks, it is essential to maintain access everywhere
and offer low latency with high reliability. To achieve such goals, satellite networks are an …

Classical edge computing algorithms assume that the execution time is always known in
resource allocation. However, in practice, the execution time in the edge server is hard to …

Cloud–edge heterogeneous network is an emerging technique built on edge infrastructure,
which is based on the core of cloud computing technology and edge computing capabilities …

Adaptive bitrate (ABR) streaming has been used in wireless networks to deal with the time-
varying wireless channels. Traditionally, wireless video is fetched from remote Internet …

Mobile edge computing (MEC) is considered a novel paradigm for computation-intensive
and delay-sensitive tasks in fifth generation (5G) networks and beyond. However, its …

Distributed machine learning (ML) algorithms are imperative for the next-generation Internet
of Things (IoT) networks, thanks to preserving the privacy of users' data and efficient usage …

As a key smart transportation service, public vehicle systems are intended to improve traffic
efficiency and vehicle occupancy ratios, and to reduce the number of vehicles on roads, by …

Given the rapid increase of various applications in vehicular networks, it is crucial to
consider a flexible architecture to improve the Quality of Service (QoS). Utilizing Multi-access …

Vehicular edge computing is viewed as a promising technique for relieving the overload of
base station (BS) on roadside, via leveraging the computation resources of vehicles on road …

Federated learning (FL) leverages the private data and computing power of multiple clients
to collaboratively train a global model. Many existing FL algorithms over wireless networks …