ACM Home Page
Please provide us with feedback. Feedback
Towards scalable location-aware services: requirements and research issues
Full text PdfPdf (195 KB)
Source Geographic Information Systems archive
Proceedings of the 11th ACM international symposium on Advances in geographic information systems table of contents
New Orleans, Louisiana, USA
Pages: 110 - 117  
Year of Publication: 2003
ISBN:1-58113-730-3
Authors
Mohamed F. Mokbel  Purdue University, West Lafayette, IN
Walid G. Aref  Purdue University, West Lafayette, IN
Susanne E. Hambrusch  Purdue University, West Lafayette, IN
Sunil Prabhakar  Purdue University, West Lafayette, IN
Sponsors
ACM: Association for Computing Machinery
SIGMIS: ACM Special Interest Group on Management Information Systems
SIGIR: ACM Special Interest Group on Information Retrieval
Publisher
ACM  New York, NY, USA
Bibliometrics
Downloads (6 Weeks): 7,   Downloads (12 Months): 57,   Citation Count: 7
Additional Information:

abstract   references   cited by   index terms   collaborative colleagues  

Tools and Actions: Request Permissions Request Permissions    Review this Article  
DOI Bookmark: Use this link to bookmark this Article: http://doi.acm.org/10.1145/956676.956691
What is a DOI?

ABSTRACT

The emergence of location-aware services calls for new real time spatio-temporal query processing algorithms that deal with large numbers of mobile objects and queries. Online query response is an important characterization of location-aware services. A delay in the answer to a query gives invalid and obsolete results, simply because moving objects can change their locations before the query responds. To handle large numbers of spatio-temporal queries efficiently, we propose the idea of sharing as a means to achieve scalability. In this paper, we introduce several types of sharing in the context of continuous spatio-temporal queries. Examples of sharing in the context of real-time spatio-temporal database systems include sharing the execution, sharing the underlying space, sharing the sliding time windows, and sharing the objects of interest. We demonstrate how sharing can be integrated into query predicates, e.g., selection and spatial join processing. The goal of this paper is to outline research directions and approaches that will lead to scalable and efficient location-aware services.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
1
 
2
W. G. Aref, S. E. Hambrusch, and S. Prabhakar. Pervasive Location Aware Computing Environments (PLACE)http://www.cs.purdue.edu/place/.
3
 
4
 
5
V. P. Chakka, A. Everspaugh, and J. M. Patel. Indexing Large Trajectory Data Sets with SETI. In Proc. of the Conf. on Innovative Data Systems Research, CIDR Asilomar, CA, Jan. 2003.
 
6
 
7
S. Chandrasekaran and M. J. Franklin. Streaming Queries over Streaming Data. In VLDB pages 203--214, Hong Kong, 2002.
 
8
J. Chen, D. J. DeWitt, and J. F. Naughton. Design and Evaluation of Alternative Selection Placement Strategies in Optimizing Continuous Queries. In ICDE San Jose, CA, 2002.
9
10
11
12
 
13
 
14
M. A. Hammad, M. J. Franklin, W. G. Aref, and A. K. Elmagarmid. Scheduling for shared window joins over data streams. In VLDB Berlin, Germany, Sept. 2003.
 
15
 
16
 
17
 
18
19
20
21
 
22
M. F. Mokbel, T. M. Ghanem, and W. G. Aref. Spatio-temporal Access ethods. IEEE Data Engineering Bulletin 26(2):4--49, June 2003.
23
 
24
 
25
26
 
27
S. Saltenis and C. S. Jensen. Indexing of Moving Objects for Location-Based Services. In ICDE SanJose, CA, Feb. 2002.
28
29
 
30
 
31
 
32
 
33
Y. Tao, D. Papadias, and Q. Shen. Continuous Nearest Neighbor Search. In VLDB pages 287--298,Hong Kong, 2002.
 
34
Y. Tao, D. Papadias, and J. Sun. The TPR*-Tree: An Optimized Spatio-temporal Access Method for Predictive Queries. In VLDB Berlin, Germany, Sept. 2003.
 
35
J. Tayeb, Ö.Ulusoy, and O. Wolfson. A Quadtree-Based Dynamic Attribute Indexing Method. The Computer Journal 41(3):185--200, 1998.
36
 
37

CITED BY  7

Collaborative Colleagues:
Mohamed F. Mokbel: colleagues
Walid G. Aref: colleagues
Susanne E. Hambrusch: colleagues
Sunil Prabhakar: colleagues