This book discusses the different facets of the problem of
compressing data pertaining to whereabouts-in-time information for mobile
entities. It gives a comprehensive overview of the state of the art in terms of
existing techniques as well as the impact of various contexts associated with
modeling and representing the motion.
The first part of this book presents a global overview of
the problem of data compression in general and throughout the history,
illustrates the different categorizations of compression approaches, and
positions the rest of the book in these settings. It discusses separately the
facets of compressing spatial data (polylines, cartography, and beyond) and
temporal data (temporal databases, time series, streaming data).
The second part of this book explores in detail the various
issues arising when compression is attempted in the realm of moving objects
management, both for point-objects and evolving shapes. It starts with
discussing the basic settings and the related solutions and fundamental techniques
common to various application and analyzes the benefits and trade-offs
associated with mobile data reduction in both online and (near) real-time
settings. It also covers the impact of the different distance functions used to
capture the quality of the compression process. Subsequently, it incorporates
the role of different contexts such as energy issues when tracking in wireless
sensor networks, known restrictions of motion (e.g., road networks), etc.
Other key topics range from the role of data compression in
clustering mobile data to the impact of various semantics-based features (such
as symbolic trajectories and warehousing of spatio-temporal data). Compression of Mobility Data concludes
with a discussion of the possible future research directions associated with
different aspects of compressing spatio-temporal data.
