Network Slicing and Deep Reinforcement Learning (DRL) are vital enablers for achieving
5G and 6G networks. A 5G/6G network can comprise various network slices from unique or …

To support rapidly increasing services and applications from users, multi-tier computing is
emerged as a promising system-level computing architecture by distributing …

Abstract The Information-Centric Internet-of-Things (IC-IoT) will connect billions of devices to
the Internet, which allows for many remarkable applications like smart homes, smart grids …

In multi-access edge computing (MEC) networks, network slicing enables the MEC network
service provider (MEC-NSP) to provide customizable MEC services for user devices (UDs) …

In network slicing, dynamic resource allocation is the key to network performance
optimization. Deep reinforcement learning (DRL) is a promising method to exploit the …

To provide various onboard entertainment services, the ever-increased Internet contents to
be exchanged among remote data centers, roadside units (RSUs), and vehicles demand …

Unmanned aerial vehicles (UAVs) have proven to be useful in a variety of applications,
including aerial base station relay. UAVs can be used to relay network access from the air to …

Content Delivery Networks (CDNs) are becoming more critical due to the tremendous
growth of video traffic. This paper proposes a complete framework targeting the creation of …

This article investigates the semantic extraction task-oriented dynamic multi-time scale user
admission and resource allocation in mobile edge computing (MEC) systems. Amid …

The world today is experiencing an enormous increase in data traffic, coupled with demand
for greater quality of experience (QoE) and performance. Increasing mobile traffic leads to …