On mobile edge caching
With the widespread adoption of various mobile applications, the amount of traffic in wireless
networks is growing at an exponential rate, which exerts a great burden on mobile core …
networks is growing at an exponential rate, which exerts a great burden on mobile core …
Resource management in cloud radio access network: Conventional and new approaches
Cloud radio access network (C-RAN) is a promising mobile wireless sensor network
architecture to address the challenges of ever-increasing mobile data traffic and network …
architecture to address the challenges of ever-increasing mobile data traffic and network …
QoS-aware fog resource provisioning and mobile device power control in IoT networks
Fog-aided Internet of Things (IoT) addresses the resource limitations of IoT devices in terms
of computing and energy capacities, and enables computational intensive and delay …
of computing and energy capacities, and enables computational intensive and delay …
Fog resource provisioning in reliability-aware IoT networks
To provide a better quality of service (QoS), cloud computing paradigm in Internet of Things
(IoT) networks has shifted toward the edge. Fog-aided IoT networks deploy fog nodes, which …
(IoT) networks has shifted toward the edge. Fog-aided IoT networks deploy fog nodes, which …
Resource allocation scheme for 5G C-RAN: a Swarm Intelligence based approach
The recent fifth generation (5G) system enabled a highly promising evolution of Cloud Radio
Access Network (C-RAN). Unlike the conventional Radio Access Network (RAN), the C-RAN …
Access Network (C-RAN). Unlike the conventional Radio Access Network (RAN), the C-RAN …
Resource allocation in 5G cloud‐RAN using deep reinforcement learning algorithms: A review
M Khani, S Jamali, MK Sohrabi… - Transactions on …, 2024 - Wiley Online Library
This paper reviews recent research on resource allocation in 5G cloud‐based radio access
networks (C‐RAN) using deep reinforcement learning (DRL) algorithms. It explores the …
networks (C‐RAN) using deep reinforcement learning (DRL) algorithms. It explores the …
QoS-aware power control in internet of drones for data collection service
Internet of Drones (IoD) utilizes drones as the Internet of Things devices to collect
information (eg, air pollutant level and traffic condition) over different points of interests, and …
information (eg, air pollutant level and traffic condition) over different points of interests, and …
Apt-RAN: A flexible split-based 5G RAN to minimize energy consumption and handovers
The recent adoption of virtualized technologies in Next Generation Radio Access Network
(NG-RAN) has driven a significant impact on energy consumption by subsequently …
(NG-RAN) has driven a significant impact on energy consumption by subsequently …
On energy efficient resource allocation in shared RANs: Survey and qualitative analysis
F Marzouk, JP Barraca… - … Communications Surveys & …, 2020 - ieeexplore.ieee.org
An expansion of services and unprecedented traffic growth is anticipated in future networks,
aligned with the adoption of the long-awaited Fifth Generation (5G) of mobile …
aligned with the adoption of the long-awaited Fifth Generation (5G) of mobile …
Task allocation in fog-aided mobile IoT by Lyapunov online reinforcement learning
Fog-aided mobile IoT is proposed to speed up service response by deploying fog nodes at
network edges. We investigate the task allocation in fog-aided mobile IoT networks, where …
network edges. We investigate the task allocation in fog-aided mobile IoT networks, where …