Cloud-Assisted Data Storage and Query Processing at Vehicular Ad-Hoc Sensor Networks

In this paper we propose an efficient cloud-assisted data storage and query processing scheme for VANETs. It integrates the cloud and vehicular networks to facilitate data storage and indexing, so queries could be processed and forwarded along different communication channels according to the cost and time bounds of the queries. Moreover, the cloud calculates a result forwarding strategy by solving a Linear Programming problem, where the query results choose the best path either through the 4G channel or through DSRC (Dedicated Short Range Communication). This research is the first step towards the integration of the cloud and the vehicular networks, as well as the 4G channel, to improve the effectiveness and speeding up of the query processing in VANETs. Extensive experiments demonstrate that up to 94% of the queries could be successfully processed in the proposed scheme, QRF much higher than existing query schemes, while at the same time with a relatively low querying cost.