A digital twin-assisted intelligent partial offloading approach for vehicular edge computing

L Zhao, Z Zhao, E Zhang, A Hawbani… - IEEE Journal on …, 2023 - ieeexplore.ieee.org
Vehicle Edge Computing (VEC) is a promising paradigm that exposes Mobile Edge
Computing (MEC) to road scenarios. In VEC, task offloading can enable vehicles to offload …

A comprehensive review on internet of things task offloading in multi-access edge computing

W Dayong, KBA Bakar, B Isyaku, TAE Eisa… - Heliyon, 2024 - cell.com
With the rapid development of Internet of Things (IoT) technology, Terminal Devices (TDs)
are more inclined to offload computing tasks to higher-performance computing servers …

DNN partition and offloading strategy with improved particle swarm genetic algorithm in VEC

C Li, L Chai, K Jiang, Y Zhang, J Liu… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Vehicular edge computing (VEC) is a novel computing paradigm, which is designed to
satisfy the growing computation and communication needs of vehicle systems. With the …

BTV-CMAB: A Bi-directional trust verification based combinatorial multi-armed bandit scheme for mobile crowdsourcing

J Tang, K Fan, W Xie, F Han, Z Qu, A Liu… - IEEE Internet of …, 2023 - ieeexplore.ieee.org
Mobile crowdsourcing (MCS) is an emerging paradigm that harnesses the collective power
of the crowd to tackle large-scale tasks. To ensure the high-quality worker selection, various …

Adaptive swarm intelligent offloading based on digital twin-assisted prediction in VEC

L Zhao, T Li, E Zhang, Y Lin, S Wan… - IEEE Transactions …, 2023 - ieeexplore.ieee.org
Vehicular Edge Computing (VEC) is the transportation version of Mobile Edge Computing
(MEC). In VEC, task offloading enables vehicles to offload computing tasks to nearby …

A survey on computation offloading in edge systems: From the perspective of deep reinforcement learning approaches

P Peng, W Lin, W Wu, H Zhang, S Peng, Q Wu… - Computer Science …, 2024 - Elsevier
Driven by the demand of time-sensitive and data-intensive applications, edge computing
has attracted wide attention as one of the cornerstones of modern service architectures. An …

Multi-compression scale DNN inference acceleration based on cloud-edge-end collaboration

H Qi, F Ren, L Wang, P Jiang, S Wan… - ACM Transactions on …, 2024 - dl.acm.org
Edge intelligence has emerged as a promising paradigm to accelerate DNN inference by
model partitioning, which is particularly useful for intelligent scenarios that demand high …

Distributed age-of-information optimization in edge computing for internet of vehicles

L Yang, Y Zou, D Yu, J Yu - Journal of Systems Architecture, 2023 - Elsevier
As an important concept to depict the freshness of an information when it arrives at the
destination, the Age-of-Information (AoI) and its relative scheduling works can be a very …

Intelligent Caching for Vehicular Dew Computing in Poor Network Connectivity Environments

L Zhao, H Li, E Zhang, A Hawbani, M Lin… - ACM Transactions on …, 2024 - dl.acm.org
In vehicular networks, some edge servers may not function properly due to the time-varying
load condition and the uneven computing resource distribution, resulting in a low quality of …

DSG-BTra: Differentially Semantic-Generalized Behavioral Trajectory for Privacy-Preserving Mobile Internet Services

G Qiu, G Tang, C Li, D Guo, Y Shen… - IEEE Internet of Things …, 2023 - ieeexplore.ieee.org
While facilitating user daily lives, the booming development of mobile Internet services
raises their privacy concerns because of the need to share travel trajectories. Due to the …