Aug. 2009 ~ May 2010
The University of Texas at Austin
Advisor: Prof. Lili Qiu
The goal is to present a system for enabling high-bandwidth content distribution in vehicular networks. In the system, a vehicle opportunistically communicates with nearby access points to download the content of interest. To fully take advantage of such transient contact with APs, we proactively push content to APs that the vehicles will likely visit in the near future. It includes two components: 1) an algorithm for predicting the APs that will soon be visited by the vehicles, and 2) a series of replication optimization techniques to enable the synergy among Internet connectivity, local wireless connectivity, and vehicular relay connectivity.
The architecture of VNet: There are APs deployed in coffee shops or gas stations. The APs can connect to Internet and download video from content distribution server or connect to each other to form a mesh network. Cars which pass through coffee shops or gas stations can associate with APs and exchange demands or requested data. Cars are also capable of inter-car communication.
We develop a prediction algorithm which find K trajectories that most closely match the vehicle’s recent history and predict APs will be visited in near future.
The improvement we have achieved.
- Upendra Shevade, , Lili Qiu, Yin Zhang, Vinoth Chandar, Mi Kyung Han, Han Hee Song, Yousuk Seung: Enabling high-bandwidth vehicular content distribution. CoNEXT 2010: 23