Continuous Range Queries over Multi-Attribute Trajectories

jianqiu Xu, Zhifeng Bao, Hua Lu

Abstract:

A multi-attribute trajectory consists of a sequence of
time-stamped locations and a set of attributes that characterize
diverse aspects of the corresponding moving object. In this
paper, we study continuous range queries over multi-attribute
trajectories. Such a query returns the objects whose attributes
contain expected values and whose locations are always within
a distance threshold to the query trajectory during the entire
overlapping time period. To efficiently answer the query, an
optimal method of partitioning the trajectories is proposed and
an index structure is developed to support the combined search
of spatio-temporal parameters and attribute values. We provide a
general solution that is able to process multi-attribute trajectories
as well as traditional trajectories without attributes. We carry
out comprehensive experiments in a prototype database system
to evaluate the efficiency and scalability of our designs. The
experimental results show that our approach outperforms five
alternative approaches by a factor of 5-50x on large datasets.