Poster: Accurate Data Aggregation for VANETs

Data aggregation is an important issue for vehicular ad-hoc networks (VANETs). Congestion notification applications are built to warn drivers of traffic slowdowns far enough in advance that the drivers may take alternate routes. Data that is broadcast should be self-contained and fit into a single MAC-layer frame. With dense traffic, aggregation is needed to represent a large number of vehicles in relatively small frame. We present a new technique for aggregating vehicles' data without losing accuracy. Vehicles build a local view based on speed and position reports from neighboring vehicles. This local view, representing vehicles up to 1.6 km ahead, is then aggregated into a single frame and broadcast. Vehicles use received aggregated frames to extend their views even farther.