Weighted Clustering with Robust Data Aggregation for Vehicular Ad Hoc Networks

  • Sridevi H, Basavaraj Mathapati


Since from last decade the Vehicular Ad hoc Networks (VANETs) plays the significant role in smart traffic monitoring and planning. Efficient vehicle data aggregation is critical to the large-scale vehicle route planning, traffic analysis, and intelligent transportation management. Due to the resources constraints in VANETs, data aggregation becomes one of the vital requirements to save the bandwidth. The recent data aggregation techniques for VANET designed with limited scope and using generalized clustering approach, however by considering the high dynamics of VANET both the clustering and data aggregation should consider the high dynamics of VANET communications. This paper proposed novel approach for weight based clustering and data aggregation called Weighted Clustering and Data Aggregation (WCDA) as VANET routing protocol. In WCDA, the Cluster Head (CH) selection and cluster formation performed by considering vehicle mobility and geographical distance based number of neighbour’s parameters to address the challenge of high dynamics. The in-Network data aggregation performed using adaptive data aggregation framework where the aggregation perform on data received from Cluster Members (CMs) at each CH node using weighted data fusion and decision making strategy to achieve the higher bandwidth efficiency with minimum data loss. The level of data aggregation at each CH node adjusted dynamically in adaptive control mechanism of data aggregation framework. The results prove that proposed protocol provides less distortion and enhancement in throughput and packet delivery ration with minimum overhead.

How to Cite
Basavaraj Mathapati, S. H. (2020). Weighted Clustering with Robust Data Aggregation for Vehicular Ad Hoc Networks. International Journal of Advanced Science and Technology, 29(3), 670 - 697. Retrieved from http://sersc.org/journals/index.php/IJAST/article/view/4135