Compression of trajectory data: a comprehensive evaluation and new approach

GPS-equipped mobile devices such as smart phones and in-car navigation units are collecting enormous amounts of spatial and temporal information that traces a moving object’s path. The exponential increase in the amount of such trajectory data has caused three major problems. First, transmission of large amounts of data is expensive and time-consuming. Second, queries on large amounts of trajectory data require computationally expensive operations to extract useful patterns and information. Third, GPS trajectories often contain large amounts of redundant data that waste storage and cause increased disk I/O time. These issues can be addressed by algorithms that reduce the size of trajectory data. A key requirement for these algorithms is to minimize the loss of information essential to locationbased applications. This paper presents a new compression method called SQUISH-E (Spatial QUalIty Simplification Heuristic Extended) that provides improved runtime performance and usability. A comprehensive comparison of SQUISH-E with J. Muckell (B) Department of Informatics, College of Computing and Information, University at Albany – State University of New York, Albany, NY 12222, USA e-mail: [email protected] P. W. Olsen Jr. · J.-H. Hwang · S. S. Ravi Department of Computer Science, College of Computing and Information, University at Albany – State University of New York, Albany, NY 12222, USA P. W. Olsen Jr. e-mail: [email protected] J.-H. Hwang e-mail: [email protected] S. S. Ravi e-mail: [email protected] C. T. Lawson Department of Geography and Planning and College of Computing and Information, University at Albany – State University of New York, Albany, NY 12222, USA e-mail: [email protected]