Hierarchical aggregation for delay-sensitive vehicular sensing

Vehicular sensing has gained significant attention in recent years, thanks to its enormous benefits to many entities including traffic management centers, forensic authorities and air pollution control units. To reduce redundancy and improve the content, the collected data must be aggregated. Delay-sensitive sensing applications require the aggregated data be collected with a certain delay. In this paper, we propose a hierarchical aggregation scheme for image sensing in vehicular networks. The hierarchy is dynamically updated based on observed network conditions. In particular, partition and merge operations are performed on the hierarchy to satisfy the delay requirement. The simulation results show that the proposed scheme outperforms existing scheme in terms of efficient data collection and redundancy elimination.