Skip to Main content Skip to Navigation
Conference papers

Smart Directional Data Aggregation in VANETs

Abstract : The ultimate goal of a Traffic Information System (TIS) consists in properly informing vehicles about road traffic conditions in order to reduce traffic jams and consequently CO2 emission while increasing the user comfort. Therefore, the design of an efficient aggregation protocol that combines correlated traffic information like location, speed and direction known as Floating Car Data (FCD) is of paramount importance. In this paper, we introduce a new TIS data aggregation protocol called Smart Directional Data Aggregation (SDDA) able to decrease the network overload while obtaining high accurate information on traffic conditions for large road sections. To this end, we introduce three levels of messages filtering: (i) filtering all FCD messages before the aggregation process based on vehicle directions and road speed limitations, (ii) integrating a suppression technique in the phase of information gathering in order to eliminate the duplicate data, and (iii) aggregating the filtered FCD data and then disseminating it to other vehicles. The performed experiments show that the SDDA outperforms existing approaches in terms of effectiveness and efficiency.
Document type :
Conference papers
Complete list of metadata

Cited literature [15 references]  Display  Hide  Download
Contributor : Julien Rabaud Connect in order to contact the contributor
Submitted on : Tuesday, January 14, 2020 - 10:21:22 PM
Last modification on : Tuesday, February 15, 2022 - 3:41:36 AM
Long-term archiving on: : Wednesday, April 15, 2020 - 6:50:06 PM


Files produced by the author(s)




Sabri Allani, Richard Chbeir, Taoufik Yeferny, Sadok Ben Yahia. Smart Directional Data Aggregation in VANETs. 32nd IEEE International Conference on Advanced Information Networking and Applications, AINA 2018, Krakow, Poland, May 16-18, 2018, May 2018, Krakow, Poland. pp.63-70, ⟨10.1109/AINA.2018.00022⟩. ⟨hal-01908063⟩



Record views


Files downloads