Abstract
We demonstrate a novel location aware services framework termed COMA for efficient compression and map-matching of road-network graph data. Key innovations include working demonstration of a new compression algorithm to eliminate nodes and edges that do not affect graph connectivity while ensuring object location map-matching accuracy. The demonstration features: (1) Algorithm to leverage compressed versions of road-network graphs for map-matching of objects locations to correct road edges without decompression, (2) Upwards of 75% compression ratio implying significant savings for road network data transmission costs, a key constraint for internet of things (IOT) devices, and (3) Use of a new controllable parameter, termed conflict factor C, whereby location aware services can trade the compression efficiency with map-matching accuracy at varying granularity. In addition to above features the demonstration features an extensible framework that enables experimentation and comparison between various compression and map-matching algorithms in a rich interactive interface. In this paper we outline data management challenges for location aware services using various scenarios for compression of a real road-network map of a large region of United States, along with both real and synthetic moving object trajectories distributed over this map. We describe the COMA framework through its map-based Graphical User Interface, ability to select the area of interest from the road-network map, and submit a compression request. COMA can export and save the compact versions of the selected area in different formats and plot the compressed graph over the original map for visual inspection to study the differences between compressed and uncompressed versions and various related statistics.