| Title | Data Collection from Smart-city Sensors through large-scale Urban Vehicular Networks |
|---|---|
| ID_Doc | 38737 |
| Authors | Khan, MA; Sargento, S; Luís, M |
| Title | Data Collection from Smart-city Sensors through large-scale Urban Vehicular Networks |
| Year | 2017 |
| Published | |
| Abstract | Efficient and cost effective data collection from smart city sensors through vehicular networks is crucial for many applications, such as travel comfort, safety and urban sensing. Static and mobile sensors data can be gathered through the vehicles that will be used as data mules and, while moving, they will be able to access road side units (RSUs), and then, send the data to a server in the cloud. Therefore, it is important to research how to use opportunistic vehicular networks to forward data packets through each other in a multi-hop fashion until they reach the destination. This paper proposes a novel data forwarding algorithm for urban vehicular networks taking into consideration the rank of each vehicle, which is based on the probability to reach a road side unit. The proposed forwarding algorithm is evaluated in the mOVERS emulator considering different forwarding decisions. Results show that, by restricting the broadcast messages in the proposed algorithm, we are able to reduce the network's overhead, therefore increasing the packet delivery ratio between the sensors and the server. |
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