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Published in 2019 at "IEEE Access"
DOI: 10.1109/access.2019.2896000
Abstract: Vehicular edge computing has emerged as a promising technology to accommodate the tremendous demand for data storage and computational resources in vehicular networks. By processing the massive workload tasks in the proximity of vehicles, the…
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Keywords:
task;
task offloading;
edge computing;
delay ... See more keywords
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Published in 2020 at "IEEE Access"
DOI: 10.1109/access.2020.2965620
Abstract: Resource-intensive applications on smart vehicles is posing difficulties to the use of traditional cloud computing for computation offloading in vehicular networks. In particular, the long transmission distance between the vehicles and the cloud center can…
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Keywords:
task;
edge computing;
computation offloading;
edge ... See more keywords
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Published in 2020 at "IEEE Internet of Things Journal"
DOI: 10.1109/jiot.2020.2978830
Abstract: Vehicular edge computing (VEC) is a new computing paradigm that has great potential to enhance the capability of vehicle terminals (VTs) to support resource-hungry in-vehicle applications with low latency and high energy efficiency. In this…
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Keywords:
offloading scheduling;
based offloading;
reinforcement learning;
deep reinforcement ... See more keywords
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Published in 2020 at "IEEE Internet of Things Journal"
DOI: 10.1109/jiot.2020.2980981
Abstract: Vehicular edge computing (VEC), which integrates mobile-edge computing (MEC) into vehicular networks, can provide more capability for executing resource-hungry applications and lower latency for connected vehicles. Distributing the result content to connected vehicles is vital…
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Keywords:
content distribution;
vehicular edge;
edge computing;
distribution ... See more keywords
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Published in 2022 at "IEEE Internet of Things Journal"
DOI: 10.1109/jiot.2021.3109003
Abstract: Vehicular edge computing (VEC) has become a promising enabler for ultrareliable and low-latency communications (URLLC) vehicular networks by providing computational resources for task offloading. In this article, we investigate an online task offloading problem for…
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Keywords:
online task;
task;
contextual clustering;
task offloading ... See more keywords
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Published in 2023 at "IEEE Internet of Things Journal"
DOI: 10.1109/jiot.2022.3221966
Abstract: By deploying computing, storage, and bandwidth resources at the user side, vehicular edge computing (VEC) provides low-delay services for vehicle users. However, due to the limited resources of edge servers, how to efficiently meet the…
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Keywords:
energy;
vehicular edge;
edge computing;
qos ... See more keywords
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Published in 2022 at "IEEE Communications Letters"
DOI: 10.1109/lcomm.2022.3196711
Abstract: Vehicular Edge Computing (VEC) enables vehicles to offload tasks to the road side units (RSUs) to improve the task performance and user experience. However, blindly offloading the vehicle’s tasks might not be an efficient solution.…
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Keywords:
reinforcement learning;
vehicular edge;
edge computing;
resource allocation ... See more keywords
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Published in 2022 at "IEEE Transactions on Industrial Informatics"
DOI: 10.1109/tii.2021.3088407
Abstract: Technological advancements of urban informatics and vehicular intelligence have enabled connected smart vehicles as pervasive edge computing platforms for a plethora of powerful applications. However, varies types of smart vehicles with distinct capacities, diverse applications…
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Keywords:
digital twin;
deep reinforcement;
multiagent deep;
edge computing ... See more keywords
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Published in 2022 at "IEEE Transactions on Intelligent Transportation Systems"
DOI: 10.1109/tits.2021.3052355
Abstract: Recent advancements in edge computing and edge caching provide a feasible solution to support a plethora of new applications such as on-demand videos, AR/VR, road surveillance. However, to apply edge caching in vehicular scenarios is…
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Keywords:
hit ratio;
vehicular edge;
analysis;
interruption ... See more keywords
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Published in 2022 at "IEEE Transactions on Intelligent Transportation Systems"
DOI: 10.1109/tits.2021.3099597
Abstract: As a distributed deep learning paradigm, federated learning (FL) provides a powerful tool for the accurate and efficient processing of on-board data in vehicular edge computing (VEC). However, FL involves the training and transmission of…
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Keywords:
problem;
federated learning;
vehicular edge;
edge computing ... See more keywords
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Published in 2023 at "IEEE Transactions on Intelligent Transportation Systems"
DOI: 10.1109/tits.2022.3230430
Abstract: In an internet of vehicle (IoV) scenario, vehicular edge computing (VEC) exploits the computing capabilities of the vehicles and roadside unit (RSU) to enhance the task processing capabilities of the vehicles. Resource management is essential…
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Keywords:
task;
vehicular edge;
task offloading;
resource allocation ... See more keywords