Internet of vehicles empowered by edge intelligence
物联网学报, 2018 By pushing computing,storage and other resources to the proximity of end devices,edge intelligence empowers network edge entities powerful information processing and content delivery capabilities,while providing efficient and low-latency service support ...
Yan ZHANG, Ke ZHANG, Jiayu CAO
doaj +2 more sources
A Power Allocation Scheme for MIMO-NOMA and D2D Vehicular Edge Computing Based on Decentralized DRL. [PDF]
Sensors (Basel), 2023 Long D, Wu Q, Fan Q, Fan P, Li Z, Fan J.
europepmc +1 more source
Federated Deep Reinforcement Learning Based Task Offloading with Power Control in Vehicular Edge Computing. [PDF]
Sensors (Basel), 2022 Moon S, Lim Y.
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Autonomous Task Offloading of Vehicular Edge Computing With Parallel Computation Queues
IEEE Transactions on Mobile ComputingThis work considers a parallel task execution strategy in vehicular edge computing (VEC) networks, where edge servers are deployed along the roadside to process offloaded computational tasks of vehicular users. To minimize the overall waiting delay among vehicular users, a novel task offloading solution is implemented based on the network cooperation ...
Sungho Cho +4 more
openaire +2 more sources
Future InternetThe fifth-generation (5G) cellular infrastructure is expected to bring about the widespread use of connected vehicles. This technological progress marks the beginning of a new era in vehicular networks, which includes a range of different types and ...
Mira M. Zarie +4 more
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Mobility aware microservice placement in vehicular edge computing
Journal of Cloud Computing: Advances, Systems and ApplicationsVehicular Edge Computing (VEC) is a decentralized paradigm for processing and managing the vast amount of data generated by connected vehicles and roadside IoT devices.
A. Surayya +4 more
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Secure and Blockchain-Based Emergency Driven Message Protocol for 5G Enabled Vehicular Edge Computing. [PDF]
Sensors (Basel), 2019 Nkenyereye L +3 more
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Computation Offloading Strategy Based on Multi-Agent Reinforcement Learning in Vehicular Edge Computing Networks. [PDF]
Sensors (Basel)Liu Y, Sun Q, Liu Z.
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HyAR-PPO: Hybrid Action Representation Learning for Incentive-Driven Task Offloading in Vehicular Edge Computing. [PDF]
Sensors (Basel)Wang W, Li M, Wu H.
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Deep learning-based caching optimization for VR 360° videos in vehicular edge computing. [PDF]
Sci RepKhan S +5 more
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