Task offloading for vehicular edge computing with edge-cloud cooperation
F Dai, G Liu, Q Mo, WH Xu, B Huang - World Wide Web, 2022 - Springer
Vehicular edge computing (VEC) is emerging as a novel computing paradigm to meet low
latency demands for computation-intensive vehicular applications. However, most existing …
latency demands for computation-intensive vehicular applications. However, most existing …
Task offloading with task classification and offloading nodes selection for MEC-Enabled IoV
The Mobile Edge Computing (MEC)-based task offloading in the Internet of Vehicles (IoV)
scenario, which transfers computational tasks to mobile edge nodes and fixed edge nodes …
scenario, which transfers computational tasks to mobile edge nodes and fixed edge nodes …
A vehicular task offloading method with eliminating redundant tasks in 5g hetnets
The combination of mobile edge computing and 5G heterogeneous networks (5G HetNets)
provides new vehicular task offloading research solutions. Most existing task offloading …
provides new vehicular task offloading research solutions. Most existing task offloading …
Cooperative computational offloading in mobile edge computing for vehicles: a model-based dnn approach
Many advancements are being made in vehicular networks, such as self-driving, dynamic
route scheduling, real-time traffic condition monitoring, and on-board infotainment services …
route scheduling, real-time traffic condition monitoring, and on-board infotainment services …
Joint offloading scheduling and resource allocation in vehicular edge computing: A two layer solution
Vehicular Edge Computing (VEC) is a promising paradigm for autonomous driving. It can
reduce delay and energy consumption of tasks. The problem of joint task offloading …
reduce delay and energy consumption of tasks. The problem of joint task offloading …
[HTML][HTML] Task migration with partitioning for load balancing in collaborative edge computing
S Moon, Y Lim - Applied Sciences, 2022 - mdpi.com
Multi-access edge computing (MEC) has emerged as a promising technology to facilitate
efficient vehicular applications, such as autonomous driving, path planning and navigation …
efficient vehicular applications, such as autonomous driving, path planning and navigation …
A survey on computation resource allocation in IoT enabled vehicular edge computing
AK Gaurav, N Sahu, AP Dash… - Complex & …, 2022 - search.proquest.com
The number of vehicles is increasing at a very high rate throughout the globe. It reached 1
billion in 2010, in 2020 it was around 1.5 billion and experts say this could reach up to 2–2.5 …
billion in 2010, in 2020 it was around 1.5 billion and experts say this could reach up to 2–2.5 …
A survey on offloading in federated cloud-edge-fog systems with traditional optimization and machine learning
The huge amount of data generated by the Internet of things (IoT) devices needs the
computational power and storage capacity provided by cloud, edge, and fog computing …
computational power and storage capacity provided by cloud, edge, and fog computing …
Computation offloading and tasks scheduling for the internet of vehicles in edge computing: A deep reinforcement learning-based pointer network approach
X Ju, S Su, C Xu, H Wang - Computer Networks, 2023 - Elsevier
Abstract In the Internet of Vehicles, vehicles can offload computation tasks to edge servers
for execution. So, execution delay of tasks and energy consumption of vehicles can be …
for execution. So, execution delay of tasks and energy consumption of vehicles can be …
SEM-O-RAN: Semantic and flexible O-RAN slicing for NextG edge-assisted mobile systems
5G and beyond cellular networks (NextG) will support the continuous execution of resource-
expensive edge-assisted deep learning (DL) tasks. To this end, Radio Access Network …
expensive edge-assisted deep learning (DL) tasks. To this end, Radio Access Network …