Distributed deep-lcc for cooperatively smoothing large-scale mixed traffic flow via connected and automated vehicles
Cooperative control of connected and automated vehicles (CAVs) promises smoother traffic
flow. In mixed traffic, where human-driven vehicles with unknown dynamics coexist, data …
flow. In mixed traffic, where human-driven vehicles with unknown dynamics coexist, data …
Enhancing handover for 5g mmwave mobile networks using jump Markov linear system and deep reinforcement learning
The Fifth Generation (5G) mobile networks use millimeter waves (mmWaves) to offer gigabit
data rates. However, unlike microwaves, mmWave links are prone to user and topographic …
data rates. However, unlike microwaves, mmWave links are prone to user and topographic …
Vehicular network edge intelligent management: A deep deterministic policy gradient approach for service offloading decision
The development of edge computing has alleviated the problem of limited vehicular
computing capabilities in VANET. The vehicular edge computing (VEC) provide resources …
computing capabilities in VANET. The vehicular edge computing (VEC) provide resources …
Towards fast and energy-efficient offloading for vehicular edge computing
M Su, C Cao, M Dai, J Li, Y Li - 2022 IEEE 28th International …, 2023 - ieeexplore.ieee.org
Vehicular edge computing (VEC) has emerged in the Internet of Vehicles (IoV) as a new
paradigm that offloads computation tasks to Road Side Units (RSU) aiming to reduce the …
paradigm that offloads computation tasks to Road Side Units (RSU) aiming to reduce the …
Optimal task allocation in vehicular fog networks requiring URLLC: An energy-aware perspective
In order to make intelligent transportation systems (ITSs) come true, execution of a large
amount of data needs to be migrated from the cloud centers to the edge nodes, especially in …
amount of data needs to be migrated from the cloud centers to the edge nodes, especially in …
Unifying futures and spot market: Overbooking-enabled resource trading in mobile edge networks
Securing necessary resources for edge computing processes via effective resource trading
becomes a critical technique in supporting computation-intensive mobile applications …
becomes a critical technique in supporting computation-intensive mobile applications …
[HTML][HTML] A comprehensive survey of energy-efficient computing to enable sustainable massive IoT networks
MH Alsharif, AH Kelechi, A Jahid… - Alexandria Engineering …, 2024 - Elsevier
Energy efficiency is a key area of research aimed at achieving sustainable and
environmentally friendly networks. With the rise in data traffic and network congestion, IoT …
environmentally friendly networks. With the rise in data traffic and network congestion, IoT …
QoS-aware joint task scheduling and resource allocation in vehicular edge computing
Vehicular edge computing (VEC) has emerged in the Internet of Vehicles (IoV) as a new
paradigm that offloads computation tasks to Road Side Units (RSU), aiming to thereby …
paradigm that offloads computation tasks to Road Side Units (RSU), aiming to thereby …
A survey on computation offloading for vehicular edge computing
S Yuan, Y Fan, Y Cai - Proceedings of the 2019 7th international …, 2019 - dl.acm.org
Vehicular Edge Computing (VEC) is a promising new paradigm that has received a lot of
attention recently. Computation Offloading (CO) can migrate computing tasks to the network …
attention recently. Computation Offloading (CO) can migrate computing tasks to the network …
Spectrum-aware Multi-hop Task Routing in Vehicle-assisted Collaborative Edge Computing
Multi-access edge computing (MEC) is a promising technology to enhance the quality of
service, particularly for low-latency services, by enabling computing offloading to edge …
service, particularly for low-latency services, by enabling computing offloading to edge …