CASCADE: Cluster-Based Accurate Syntactic Compression of Aggregated Data in VANETs

We present a method for accurate aggregation of highway traffic information in vehicular ad hoc networks (VANETs). Highway congestion notification applications need to disseminate information about traffic conditions to distant vehicles. In dense traffic, aggregation is needed to allow a single frame to carry information about a large number of vehicles. Our technique, CASCADE, uses compression to provide aggregation without losing accuracy. We show that CASCADE makes efficient use of the wireless channel while providing each vehicle with data that is highly accurate, represents a large area in front of the vehicle, and can be combined with aggregated data from other vehicles to further extend the covered area.