Name
Abstract | ||
|---|---|---|
The ability of road vehicles to efficiently execute different sensing tasks varies because of the heterogeneity in their sensing ability and trajectories. Therefore, the data collection sensing task, which requires tempo-spatial sensing data, becomes a serious problem in vehicular sensing systems, particularly those with limited sensing capabilities. A utility-based sensing task decomposition and offloading algorithm is proposed in this paper. The utility function for a task executed by a certain vehicle is built according to the mobility traces and sensing interfaces of the vehicle, as well as the sensing data type and tempo-spatial coverage requirements of the sensing task. Then, the sensing tasks are decomposed and offloaded to neighboring vehicles according to the utilities of the neighboring vehicles to the decomposed sensing tasks. Real trace-driven simulation shows that the proposed task offloading is able to collect much more comprehensive and uniformly distributed sensing data than other algorithms. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.3390/s16071090 | SENSORS |
Keywords | Field | DocType |
vehicular crowd sensing,mobile crowd sensing,task offloading | Data collection,Sensing system,Simulation,Sensing data,Electronic engineering,Real-time computing,Engineering,Accident prevention,Trajectory | Journal |
Volume | Issue | Citations |
16 | 7.0 | 1 |
PageRank | References | Authors |
0.35 | 32 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yazhi Liu | 1 | 1 | 0.35 |
| Wendong Wang | 2 | 821 | 72.69 |
| Yuekun Ma | 3 | 1 | 0.69 |
| Zhigang Yang | 4 | 1 | 0.35 |
| FuXing Yu | 5 | 1 | 0.35 |