Name
Abstract | ||
|---|---|---|
With the popularization of intelligent transport and mobile internet services, vehicles and people on board generate increasing amounts of data. To match future networks with this use case, tools are needed to analyze the requirements set for the network. In this paper, we study the characteristics of data traffic in the context of networked vehicles. We generate data traffic based on real-world vehicle traces and reported data patterns of end-user applications and vehicles. Based on this, we propose a two-level hidden Markov model to describe both large and small temporal characteristics of data traffic from vehicles aggregated on base stations. We evaluate the proposed model by comparing the original and synthesized data. The results show that the proposed model can well characterize the data traffic from vehicles. |
Year | Venue | Field |
|---|---|---|
2017 | IOT | Base station,Mobile internet,Data traffic,Data patterns,Computer science,Internet of Things,Computer network,Hidden Markov model |
DocType | Citations | PageRank |
Conference | 0 | 0.34 |
References | Authors | |
13 | 9 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yuhong Li | 1 | 19 | 7.47 |
| Xiaoyu Hao | 2 | 0 | 0.34 |
| Han Zheng | 3 | 70 | 3.86 |
| Xiang Su | 4 | 157 | 26.32 |
| Jukka Riekki | 5 | 701 | 85.55 |
| Chao Sun | 6 | 5 | 9.22 |
| Hanyu Wei | 7 | 0 | 0.34 |
| Hao Wang | 8 | 440 | 127.79 |
| Lei Han | 9 | 45 | 11.52 |