A Vehicle-Assisted Computation Offloading Algorithm Based on Proximal Policy Optimization in Vehicle Edge Networks
نویسندگان
چکیده
Abstract With the continuous development of Internet Vehicles(IoV), Vehicle Edge Computing(VEC) has become a key technology for computational resource scheduling, but more and smart devices are connected to internet, which makes it difficult traditional Networks(VEN) deal with tasks in time. In this paper, order cope challenges large number accessing we propose vehicle-assisted computation offloading algorithm based on proximal policy optimization(VCOPPO) User Equipment(UE) tasks, combines dynamic parked vehicles incentives mechanism allocation strategy by using road as edge servers. Firstly, non-convex optimization problem combining VEN utility task processing delay is formulated, subject constraints residual energy transmission rate task. Secondly, proposed VCOPPO used solve formulated problem, use stochastic obtain optimal decisions schemes. Finally, experimental results have shown that an excellent performance network reward respectively, can effectively schedule allocate resources. Compared Dueling Deep Q Network(Dueling DQN), Network(DQN) Q-learning methods, improves 31%, 18% 91%, reduces 78%, 63% 74%, respectively.
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ژورنال
عنوان ژورنال: Mobile Networks and Applications
سال: 2022
ISSN: ['1383-469X', '1572-8153']
DOI: https://doi.org/10.1007/s11036-022-02029-y