Data aggregation for Vehicular Ad-hoc Network using particle swarm optimization

The data aggregation process can be considered a problem of multi-objective optimization which reduces the size of data in such a way that its relevance with original data remains as closer as possible. Data Aggregation is of great importance in Wireless Sensor Networks, Vehicular Ad-hoc Networks to transmit the recorded data in time over low bandwidth. In this regard, data aggregation solutions have been developed; however, their actual usage has been limited, for the reason of low accuracy and high processing time. In this paper, particle swarm optimization (PSO) is used to optimize process of multi-objective data aggregation in vehicular ad-hoc network. In our work processing time for aggregation and aggregation quality have been set as objectives. The proposed method has been compared with state of the art existing aggregation techniques. Experimental results show that our method simplifies aggregation effectively and obtains a higher aggregation accuracy compared to the other data aggregation methods.