Paper Info
Title
An Evaluation Of Compression Algorithms Applied To Moving Object Trajectories
Abstract
The amount of spatiotemporal data collected by gadgets is rapidly growing, resulting in increasing costs to transfer, process and store it. In an attempt to minimize these costs several algorithms were proposed to reduce the trajectory size. However, to choose the right algorithm depends on a careful analysis of the application scenario. Therefore, this paper evaluates seven general purpose lossy compression algorithms in terms of structural aspects and performance characteristics, regarding four transportation modes: Bike, Bus, Car and Walk. The lossy compression algorithms evaluated are: Douglas-Peucker (DP), Opening-Window (OW), Dead-Reckoning (DR), Top-Down Time-Ratio (TS), Opening-Window Time-Ratio (OS), STTrace (ST) and SQUISH (SQ). Pareto Efficiency analysis pointed out that there is no best algorithm for all assessed characteristics, but rather DP applied less error and kept length better-preserved, OW kept speed better-preserved, ST kept acceleration better-preserved and DR spent less execution time. Another important finding is that algorithms that use metrics that do not keep time information have performed quite well even with characteristics time-dependent like speed and acceleration. Finally, it is possible to see that DR had the most suitable performance in general, being among the three best algorithms in four of the five assessed performance characteristics.
Year
DOI
Venue
2020
10.1080/13658816.2019.1676430
INTERNATIONAL JOURNAL OF GEOGRAPHICAL INFORMATION SCIENCE
Keywords
Field
DocType
Compression trajectory algorithm, simplifying trajectory algorithms, perpendicular distance, asynchronous Euclidean distance, performance assessment
Data mining,Computer science,Data compression
Journal
Volume
Issue
ISSN
34
3
1365-8816
Citations 
PageRank 
References 
0
0.34
0
Authors
2
Name
Order
Citations
PageRank
Yoran E. Leichsenring100.34
Fabiano Baldo2155.41