286
Alminas ˇ
Civilis, Christian S. Jensen, and Stardas Pakalnis
position) and compares this with a local copy of the position that the server-side
database assumes. When needed in order to maintain the required accuracy in the
database, the object issues an update to the server. The database may predict the
future positions of a moving object in different ways.
The challenge is then how to predict the future positions of a moving object
so that the number of updates is reduced. This in turn results in reduced communication and server-side update processing. The chapter initially covers three basic
techniques for predicting the future positions of a moving object. The first two are
point- and vector-based tracking, where an object is assumed to be stationary and
to move according to a velocity vector, respectively. In the third approach, segmentbased tracking, the future movement of an object is represented by a road segment
drawn from a representation of the underlying road network and a fixed speed.
A road segment is a polyline, that is, a sequence of connected line segments. So,
this representation assumes that a moving object moves along a known road segment
at constant speed.
As explained above, a moving object is aware of the server-side representation
of its movement. The server uses this representation for predicting the current position of the moving object. The client-side moving object uses the representation for
ensuring that the server’s predicted position is within the predefined accuracy.
The chapter also covers techniques that aim to improve the basic segment-based
approach. The chapter considers modifications of the segments that make up the representation of the road network. The chapter covers the use of anticipated routes for
the moving objects, which are represented as (long) polylines, instead of individual
segments drawn from the road network representation. The chapter explores the use
of acceleration profiles instead of modeling the speed of an object as being constant
in between updates.
In summary, the chapter covers three types of techniques that aim to reduce the
communication and the update costs associated with the tracking of moving objects
with accuracy guarantees, and it reports on empirical evaluations of these techniques
and the best existing tracking techniques based on real data.
Chapter 9 concerns access control for LBSs – the reader is referred to that chapter
for further information on this highly relevant aspect of tracking.
The coverage of tracking techniques is primarily based on proposals by ˇ
Civilis
et al. [4, 5] and Jensen et al. [11]. These works share the general approach with
Wolfson et al. [22, 24]. The chapter offers results of new empirical performances
studies, based on two real GPS data sets, of the techniques presented. A more detailed
coverage of related studies is given in Sect. 13.8.
The presentation is organized as follows. Section 13.2 describes the general approach to tracking and describes the data sets used in experiments. Section 13.3
describes point-, vector-, and segment-based tracking. Section 13.4 covers improvements in the segment-based approach using road network modifications.
Sections 13.5 and 13.6 present techniques for update reduction using routes and acceleration profiles, respectively. Section 13.7 is a summary, and Sect. 13.8 covers
commercial developments and points to further readings.
Alminas ˇ
Civilis, Christian S. Jensen, and Stardas Pakalnis
position) and compares this with a local copy of the position that the server-side
database assumes. When needed in order to maintain the required accuracy in the
database, the object issues an update to the server. The database may predict the
future positions of a moving object in different ways.
The challenge is then how to predict the future positions of a moving object
so that the number of updates is reduced. This in turn results in reduced communication and server-side update processing. The chapter initially covers three basic
techniques for predicting the future positions of a moving object. The first two are
point- and vector-based tracking, where an object is assumed to be stationary and
to move according to a velocity vector, respectively. In the third approach, segmentbased tracking, the future movement of an object is represented by a road segment
drawn from a representation of the underlying road network and a fixed speed.
A road segment is a polyline, that is, a sequence of connected line segments. So,
this representation assumes that a moving object moves along a known road segment
at constant speed.
As explained above, a moving object is aware of the server-side representation
of its movement. The server uses this representation for predicting the current position of the moving object. The client-side moving object uses the representation for
ensuring that the server’s predicted position is within the predefined accuracy.
The chapter also covers techniques that aim to improve the basic segment-based
approach. The chapter considers modifications of the segments that make up the representation of the road network. The chapter covers the use of anticipated routes for
the moving objects, which are represented as (long) polylines, instead of individual
segments drawn from the road network representation. The chapter explores the use
of acceleration profiles instead of modeling the speed of an object as being constant
in between updates.
In summary, the chapter covers three types of techniques that aim to reduce the
communication and the update costs associated with the tracking of moving objects
with accuracy guarantees, and it reports on empirical evaluations of these techniques
and the best existing tracking techniques based on real data.
Chapter 9 concerns access control for LBSs – the reader is referred to that chapter
for further information on this highly relevant aspect of tracking.
The coverage of tracking techniques is primarily based on proposals by ˇ
Civilis
et al. [4, 5] and Jensen et al. [11]. These works share the general approach with
Wolfson et al. [22, 24]. The chapter offers results of new empirical performances
studies, based on two real GPS data sets, of the techniques presented. A more detailed
coverage of related studies is given in Sect. 13.8.
The presentation is organized as follows. Section 13.2 describes the general approach to tracking and describes the data sets used in experiments. Section 13.3
describes point-, vector-, and segment-based tracking. Section 13.4 covers improvements in the segment-based approach using road network modifications.
Sections 13.5 and 13.6 present techniques for update reduction using routes and acceleration profiles, respectively. Section 13.7 is a summary, and Sect. 13.8 covers
commercial developments and points to further readings.