Survey on Indexing Trajectory Data

PhD Qualifying Examination


Title: "Survey on Indexing Trajectory Data"

by

Mr. Keyu WANG


Abstract:

The proliferation of geo-positioned vehicles and mobile devices produces 
abundant trajectory data. Rich trajectory data bloom location-based services 
and improve daily life. However, query latency and stale response harm user 
experience and thus lead to loss of subscribers. Intensively update and query 
call for efficient indexing methods with low maintenance overhead.

This work surveys the state-of-art trajectory data indexing methods, which can 
be roughly classified into four categories based on their fundamental 
structures: 1) R-tree based indexes, 2) B-tree based indexes, 3) hierarchical 
indexes, and 4) other indexes. R-tree based indexes provide efficient query 
responses; B-tree based indexes focus on fast updates; Hierarchical indexes 
preserve the unique characteristics of spatial and temporal dimensions as much 
as possible. Besides the above three major categories, there are several other 
indexing methods adopting additional techniques to index trajectory data. We 
compare representatives from each category, and conclude this survey by 
discussing future directions of trajectory data indexing in the era of big 
data.


Date:			Thursday, 27 March 2014

Time:                   9:30am - 11:30am

Venue:                  Room 3501
                         Lifts 25/26

Committee Members:	Dr. Yunhao Liu (Supervisor)
 			Prof. Lionel Ni (Supervisor)
  			Dr. Lei Chen (Chairperson)
  			Prof. Shing-Chi Cheung
  			Dr. Ke Yi


**** ALL are Welcome ****