Name
Abstract | ||
|---|---|---|
Renewable energy powered road side units(RSUs) in Internet of Vehicles(IoVs) are a desirable green alternative choice compared to the traditional electric grid, because it not only extends the service range of IoVs but also saves the cost on energy. However, the energy on RSUs is limited and usually influenced by communication policies. Therefore, the communication scheduling policy on RSUs plays an important role on the persistence of network, which is still an open topic to be solved. In this paper, we focus on the communication scheduling problem on RSUs, and propose an LSTM-based communication scheduling algorithm for RSUs in IoVs. The scheduling algorithm is composed of three parts - deep learning clustering, LSTM-based traffic prediction, and a vehicle access scheduling algorithm. At last, we conduct an extensive simulation, and the simulation results indicate that our algorithm can achieve a better performance than the no scheduling mechanism. |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1109/VTC2020-Fall49728.2020.9348859 | 2020 IEEE 92nd Vehicular Technology Conference (VTC2020-Fall) |
Keywords | DocType | ISSN |
Renewable energy powered RSUs,IoVs,LSTM,Scheduling algorithms | Conference | 1090-3038 |
ISBN | Citations | PageRank |
978-1-7281-9485-1 | 0 | 0.34 |
References | Authors | |
0 | 6 | |