poster

Efficient indexing structure for scalable processing of spatial alarms

Authors:

Myungcheol Doo,

Ling Liu,

Nitya Narasimhan,

Venu VasudevanAuthors Info & Claims

GIS '10: Proceedings of the 18th SIGSPATIAL International Conference on Advances in Geographic Information Systems

Pages 426 - 429

https://doi.org/10.1145/1869790.1869853

Published: 02 November 2010 Publication History

Get Access

Abstract

We present the design and implementation of a new indexing technique, Mondrian tree. The Mondrian tree indexing method partitions the entire universe of discourse into spatial alarm monitoring regions and alarm-free regions. This enables us to reduce the number of on-demand alarm-free region computations, significant savings of both server load and client-to-server communication cost. We evaluate the efficiency of the Mondrian tree indexing approach and show that the Mondrian tree offers significant performance enhancements on spatial alarm processing at both the server side and the client side.

References

[1]

Locale. http://www.twofortyfouram.com/.

Google Scholar

[2]

Spatial data transfer format. http://www.mcmcweb.er.usgs.gov/sdts/.

Google Scholar

[3]

Us geological survey. http://www.usgs.gov/.

Google Scholar

[4]

B. Bamba, L. Liu, A. Iyengar, and P. S. Yu. Distributed processing of spatial alarms: A safe region-based approach. ICDCS, 2009.

Digital Library

Google Scholar

[5]

B. Gedik and L. Liu. Location privacy in mobile systems: A personalized anonymization model. In Proc. IEEE ICDCS, 2005.

Digital Library

Google Scholar

[6]

P. Pesti, B. Bamba, M. Doo, L. Liu, B. Palanisamy, and M. Weber. Gtmobisim: A mobile trace generator for road networks. Technical report, 2009.

Google Scholar

[7]

S. Prabhakar, Y. Xia, D. V. Kalashnikov, W. G. Aref, and S. E. Hambrusch. Query indexing and velocity constrained indexing: Scalable techniques for continuous queries on moving objects. In IEEE Transactions on Computers, 2002.

Digital Library

Google Scholar

[8]

V. Raghunathan, T. Pering, R. Want, A. Nguyen, and P. Jensen. Experience with a low power wireless mobile computing platform. In Proc. of International Symposium on Low power Electronics and Design, 2004.

Digital Library

Google Scholar

Cited By

View all

Lee KLiu LPalanisamy BYigitoglu E(2016)Road Network-Aware Spatial AlarmsIEEE Transactions on Mobile Computing10.1109/TMC.2015.240554315:1(188-201)Online publication date: 1-Jan-2016
https://dl.acm.org/doi/10.1109/TMC.2015.2405543
Liu LPalanisamy BPu CYigitoglu ELee KHan B(2013)RoadAlarmProceedings of the 2013 IEEE International Conference on Data Engineering (ICDE 2013)10.1109/ICDE.2013.6544947(1372-1375)Online publication date: 8-Apr-2013
https://dl.acm.org/doi/10.1109/ICDE.2013.6544947
Jeong-Gwan Kang Namhoon Kim Sungmin Park Kyongha Park HyunSu Hong (2013)How to extend battery life in location alarm2013 IEEE International Conference on Consumer Electronics (ICCE)10.1109/ICCE.2013.6486773(13-14)Online publication date: Jan-2013
https://doi.org/10.1109/ICCE.2013.6486773
Show More Cited By

Index Terms

Efficient indexing structure for scalable processing of spatial alarms
1. Human-centered computing
  1. Visualization
    1. Visualization application domains
      1. Geographic visualization
2. Information systems
  1. Information retrieval
    1. Document representation
    2. Search engine architectures and scalability
      1. Search engine indexing
  2. Information systems applications
    1. Spatial-temporal systems

Recommendations

An Energy Efficient Middleware Architecture for Processing Spatial Alarms on Mobile Clients

Time based alarms are used by many on a daily basis. Spatial alarms extend the very same idea to location based triggers, which are fired whenever a mobile user enters the spatial region of the location alarms. Spatial alarms provide critical ...
Distributed Processing of Spatial Alarms: A Safe Region-Based Approach
ICDCS '09: Proceedings of the 2009 29th IEEE International Conference on Distributed Computing Systems

Spatial alarms are considered as one of the basic capabilities in future mobile computing systems for enabling personalization of location-based services. In this paper, we propose a distributed architecture and a suite of safe region techniques for ...
An efficient parallel indexing structure for multi-dimensional big data using spark
Abstract
With the increasing daily production of data in recent years, indexing, storing and retrieving huge amounts of data have become a common problem, especially for multi-dimensional big data. Although R-tree has proved to be efficient for indexing ...

Comments

Information & Contributors

Information

Published In

GIS '10: Proceedings of the 18th SIGSPATIAL International Conference on Advances in Geographic Information Systems

November 2010

566 pages

ISBN:9781450304283

DOI:10.1145/1869790

General Chairs:
Divyakant Agrawal
University of California at Santa Barbara
,
Pusheng Zhang
Microsoft Corporation
,
Program Chairs:
Amr El Abbadi
University of California, Santa Barbara
,
Mohamed Mokbel
University of Minnesota

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 02 November 2010

Permissions

Request permissions for this article.

Request Permissions

Check for updates

Author Tags

Qualifiers

Poster

Conference

GIS '10

Sponsor:

SIGSPATIAL

GIS '10: 18th SIGSPATIAL International Conference on Advances in Geographic Information Systems

November 2 - 5, 2010

California, San Jose

Acceptance Rates

Overall Acceptance Rate 257 of 1,238 submissions, 21%

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

4
Total Citations
View Citations
134
Total Downloads

Downloads (Last 12 months)0
Downloads (Last 6 weeks)0

Reflects downloads up to 06 Jan 2025

Other Metrics

View Author Metrics

Citations

Cited By

View all

Lee KLiu LPalanisamy BYigitoglu E(2016)Road Network-Aware Spatial AlarmsIEEE Transactions on Mobile Computing10.1109/TMC.2015.240554315:1(188-201)Online publication date: 1-Jan-2016
https://dl.acm.org/doi/10.1109/TMC.2015.2405543
Liu LPalanisamy BPu CYigitoglu ELee KHan B(2013)RoadAlarmProceedings of the 2013 IEEE International Conference on Data Engineering (ICDE 2013)10.1109/ICDE.2013.6544947(1372-1375)Online publication date: 8-Apr-2013
https://dl.acm.org/doi/10.1109/ICDE.2013.6544947
Jeong-Gwan Kang Namhoon Kim Sungmin Park Kyongha Park HyunSu Hong (2013)How to extend battery life in location alarm2013 IEEE International Conference on Consumer Electronics (ICCE)10.1109/ICCE.2013.6486773(13-14)Online publication date: Jan-2013
https://doi.org/10.1109/ICCE.2013.6486773
Lee KLiu LMeng SPalanisamy B(2012)Scaling Spatial Alarm Services on Road NetworksProceedings of the 2012 IEEE 19th International Conference on Web Services10.1109/ICWS.2012.93(98-105)Online publication date: 24-Jun-2012
https://dl.acm.org/doi/10.1109/ICWS.2012.93

View Options

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Cited By

Index Terms

Recommendations

An Energy Efficient Middleware Architecture for Processing Spatial Alarms on Mobile Clients

Distributed Processing of Spatial Alarms: A Safe Region-Based Approach

An efficient parallel indexing structure for multi-dimensional big data using spark