Publication Type
Journal Article
Version
acceptedVersion
Publication Date
11-2004
Abstract
Owing to the advent of wireless networking and personal digital devices, information systems in the era of mobile computing are expected to be able to handle a tremendous amount of traffic and service requests from the users. Wireless data broadcast, thanks to its high scalability, is particularly suitable for meeting such a challenge. Indexing techniques have been developed for wireless data broadcast systems in order to conserve the scarce power resources in mobile clients. However, most of the previous studies do not take into account the impact of location information of users. In this paper, we address the issues of supporting spatial queries (including window queries and kNN queries) of location-dependent information via wireless data broadcast. A linear index structure based on the Hilbert curve and corresponding search algorithms are proposed to answer spatial queries on air. Experiments are conducted to evaluate the performance of the proposed indexing technique. Results show that the proposed index and its enhancement outperform existing algorithms significantly.
Keywords
location-dependent spatial queries, wireless broadcast, index structure, pervasive computing
Discipline
Databases and Information Systems | Numerical Analysis and Scientific Computing
Publication
Wireless Networks
Volume
10
Issue
6
First Page
723
Last Page
736
ISSN
1022-0038
Identifier
10.1023/B:WINE.0000044031.03597.97
Publisher
Springer Verlag
Citation
ZHENG, Baihua; LEE, Wang-Chien; and LEE, Dik Lun.
Spatial Queries in Wireless Broadcast Systems. (2004). Wireless Networks. 10, (6), 723-736.
Available at: https://ink.library.smu.edu.sg/sis_research/1090
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Additional URL
http://dx.doi.org/10.1023/B:WINE.0000044031.03597.97
Included in
Databases and Information Systems Commons, Numerical Analysis and Scientific Computing Commons