Name
Abstract | ||
|---|---|---|
With the emergence of the ever-increasing vehicular applications and booming Internet services, the requirements of low-latency and high efficient transmission among vehicles become urgent to meet, and their corresponding solutions need to be well investigated. To resolve the above challenges, we propose a fog computing-based content transmission scheme with collective filtering in edge of vehicles. We first provide a system model based on fog-based rode side units by considering location-awareness, content-caching and decentralized computing. Then, a content-caching strategy in RSUs is designed to minimize the downloading latency. Specifically, we model the moving vehicles with the two-dimensional Markov chains, and calculate the probabilities of file caching in RSUs to minimize the latency in file downloading. Each vehicle can also maintain a neighbor list to record the encounters with high similarities, and update it based on the historic and real-time contacts. Finally, we carry on the experiments based on the real-world taxi trajectories in Beijing and Shanghai, China. Simulation results demonstrate the effectiveness of our proposed method. |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1016/j.ins.2019.07.083 | Information Sciences |
Keywords | Field | DocType |
Edge of vehicles,Collaborative filtering,Fog computing,Markov chains | Decentralized computing,Latency (engineering),Upload,Markov chain,Computer network,Filter (signal processing),Artificial intelligence,System model,Machine learning,Beijing,Mathematics,The Internet | Journal |
Volume | ISSN | Citations |
506 | 0020-0255 | 1 |
PageRank | References | Authors |
0.35 | 0 | 7 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Xiaojie Wang | 1 | 306 | 22.81 |
| Yufan Feng | 2 | 1 | 0.69 |
| Zhaolong Ning | 3 | 553 | 50.11 |
| Xiping Hu | 4 | 719 | 56.30 |
| Xiangjie Kong | 5 | 425 | 46.56 |
| Bin Hu | 6 | 778 | 107.21 |
| Yi Guo | 7 | 1 | 0.35 |