A comprehensive survey of network function virtualization

B Yi, X Wang, K Li, M Huang - Computer Networks, 2018 - Elsevier
Today's networks are filled with a massive and ever-growing variety of network functions that
coupled with proprietary devices, which leads to network ossification and difficulty in network …

Recent advances of resource allocation in network function virtualization

S Yang, F Li, S Trajanovski… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
Network Function Virtualization (NFV) has been emerging as an appealing solution that
transforms complex network functions from dedicated hardware implementations to software …

Joint task offloading and resource allocation for energy-constrained mobile edge computing

H Jiang, X Dai, Z Xiao, A Iyengar - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
We consider the problem of task offloading and resource allocation in mobile edge
computing (MEC). To maintain satisfactory quality of experience (QoE) of end-users, mobile …

UAV-assisted task offloading in vehicular edge computing networks

X Dai, Z Xiao, H Jiang, JCS Lui - IEEE Transactions on Mobile …, 2023 - ieeexplore.ieee.org
Vehicular edge computing (VEC) provides an effective task offloading paradigm by pushing
cloud resources to the vehicular network edges, eg, road side units (RSUs). However …

Deep reinforcement learning for user association and resource allocation in heterogeneous cellular networks

N Zhao, YC Liang, D Niyato, Y Pei… - IEEE Transactions on …, 2019 - ieeexplore.ieee.org
Heterogeneous cellular networks can offload the mobile traffic and reduce the deployment
costs, which have been considered to be a promising technique in the next-generation …

Follow me at the edge: Mobility-aware dynamic service placement for mobile edge computing

T Ouyang, Z Zhou, X Chen - IEEE Journal on Selected Areas in …, 2018 - ieeexplore.ieee.org
Mobile edge computing is a new computing paradigm, which pushes cloud computing
capabilities away from the centralized cloud to the network edge. However, with the sinking …

Joint configuration adaptation and bandwidth allocation for edge-based real-time video analytics

C Wang, S Zhang, Y Chen, Z Qian… - IEEE INFOCOM 2020 …, 2020 - ieeexplore.ieee.org
Real-time analytics on video data demands intensive computation resources and high
energy consumption. Traditional cloud-based video analytics relies on large centralized …

Distributed and dynamic service placement in pervasive edge computing networks

Z Ning, P Dong, X Wang, S Wang, X Hu… - … on Parallel and …, 2020 - ieeexplore.ieee.org
The explosive growth of mobile devices promotes the prosperity of novel mobile
applications, which can be realized by service offloading with the assistance of edge …

Traffic-aware and energy-efficient vNF placement for service chaining: Joint sampling and matching approach

C Pham, NH Tran, S Ren, W Saad… - IEEE Transactions on …, 2017 - ieeexplore.ieee.org
Although network function virtualization (NFV) is a promising approach for providing elastic
network functions, it faces several challenges in terms of adaptation to diverse network …

When UAV swarm meets edge-cloud computing: The QoS perspective

W Chen, B Liu, H Huang, S Guo, Z Zheng - IEEE Network, 2019 - ieeexplore.ieee.org
In this article, we propose a hybrid computing model, UAV-Edge-Cloud, bringing edge/cloud
computing and UAV swarm together to achieve high quality of service (QoS) guarantees …