A joint service migration and mobility optimization approach for vehicular edge computing
The vehicular edge computing is considered an enabling technology for intelligent and
connected vehicles since the optimization of communication and computing on edge has a …
connected vehicles since the optimization of communication and computing on edge has a …
Deep reinforcement learning for collaborative edge computing in vehicular networks
Mobile edge computing (MEC) is a promising technology to support mission-critical
vehicular applications, such as intelligent path planning and safety applications. In this …
vehicular applications, such as intelligent path planning and safety applications. In this …
Joint service caching and computation offloading scheme based on deep reinforcement learning in vehicular edge computing systems
Vehicular edge computing (VEC) is a new computing paradigm that enhances vehicular
performance by introducing both computation offloading and service caching, to resource …
performance by introducing both computation offloading and service caching, to resource …
Toward reliable DNN-based task partitioning and offloading in vehicular edge computing
Modern vehicles have become typical consumer electronics with the development of
sensing, transmission, and computation technologies. The emerging intelligent …
sensing, transmission, and computation technologies. The emerging intelligent …
Knowledge-driven service offloading decision for vehicular edge computing: A deep reinforcement learning approach
The smart vehicles construct Internet of Vehicle (IoV), which can execute various intelligent
services. Although the computation capability of a vehicle is limited, multi-type of edge …
services. Although the computation capability of a vehicle is limited, multi-type of edge …
Matching-based task offloading for vehicular edge computing
P Liu, J Li, Z Sun - IEEE Access, 2019 - ieeexplore.ieee.org
Vehicular edge computing has emerged as a promising technology to accommodate the
tremendous demand for data storage and computational resources in vehicular networks. By …
tremendous demand for data storage and computational resources in vehicular networks. By …
Energy-delay minimization of task migration based on game theory in MEC-assisted vehicular networks
Roadside units (RSUs), which have strong computing capability and are close to vehicle
nodes, have been widely used to process delay-and computation-intensive tasks of vehicle …
nodes, have been widely used to process delay-and computation-intensive tasks of vehicle …
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 …
An efficient task offloading scheme in vehicular edge computing
Vehicular edge computing (VEC) is a promising paradigm to offload resource-intensive
tasks at the network edge. Owing to time-sensitive and computation-intensive vehicular …
tasks at the network edge. Owing to time-sensitive and computation-intensive vehicular …
Task offloading in vehicular edge computing networks via deep reinforcement learning
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 …
consider a flexible architecture to improve the Quality of Service (QoS). Utilizing Multi-access …