ACM Home Page
Please provide us with feedback. Feedback
Hoarding location-based data using clustering
Full text PdfPdf (586 KB)
Source MOBIWAC archive
Proceedings of the 4th ACM international workshop on Mobility management and wireless access table of contents
Terromolinos, Spain
SESSION: Multimedia, data distribution and session management table of contents
Pages: 164 - 171  
Year of Publication: 2006
ISBN:1-59593-488-X
Authors
Susanne Bürklen  Universitaet Stuttgart, Stuttgart, Germany
Pedro José Marrón  Universitaet Stuttgart, Stuttgart, Germany
Kurt Rothermel  Universitaet Stuttgart, Stuttgart, Germany
Timo Pfahl  Universitaet Stuttgart, Stuttgart, Germany
Sponsors
ACM: Association for Computing Machinery
SIGSIM: ACM Special Interest Group on Simulation and Modeling
Publisher
ACM  New York, NY, USA
Bibliometrics
Downloads (6 Weeks): 6,   Downloads (12 Months): 34,   Citation Count: 0
Additional Information:

abstract   references   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/10.1145/1164783.1164815
What is a DOI?

ABSTRACT

The proliferation of mobile devices and the fact that high-bandwidth and continuous connectivity is not available everywhere, has led to the creation of hoarding algorithms that attempt to mitigate the problems related with disconnected operation and with the operation in areas where bandwidth is either scarce or expensive. In this paper, we present a hoarding scheme for location-based data in semi-structured information spaces, such as the World Wide Web, which relies on clustering of semantically related data items. We show by means of experimental evaluation that our clustering-based approach outperforms existing hoarding techniques that do not make use of clustering by a factor of more than 2 in terms of hoard cache hit ratio.


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
D. Badrinath, T. Imielinski, R. Frenkiel, and D. Goodman. Nimble: Many-time, many-where communication support for information systems in highly mobile and wireless environments. http://www.cs.rutgers.edu/dataman/nimble/, 1996.
 
3
Albert-László Barabási and Eric Bonabeau. Scale-free networks. Scientific American, May 2003.
4
 
5
 
6
Susanne Bürklen, Pedro José Marrón, and Kurt Rothermel. An enhanced hoarding approach based on graph analysis. In Proc. of the IEEE Int. Conf. on Mobile Data Management (MDM 2004), Berkeley, CA, USA, pages 358--369, 2004.
7
8
 
9
 
10
Jim Griffioen and Randy Appleton. Reducing file system latency using a predictive approach. In USENIX Summer, pages 197--207, 1994.
11
12
13
14
 
15
Kwong Lai and Zahir Tari and Peter Bertok. Supporting Disconnected Operations Through Cooperative Hoarding. In Proc. of Int. Conf. on Computer Communications and Networks (ICCCN), October 2005.
16
 
17
18
 
19
O. Ratsimor and S. Balaji Kodeswaran and A. Joshi and T. Finin and Y. Yesha. Combining Infrastructure and Ad hoc Collaboration For Data Management in Mobile Wireless Networks. In Workshop on Ad hoc Communications and Collaboration in Ubiquitous Computing Environments, 2002.
20
21
 
22
A. Reyes-Lecuona, E. González-Parada, E. Casilari, and A. Díaz-Estrella. A page-oriented www traffic model for wireless system simulations. In Proceddings of the 16th Int. Teletraffic Congress (ITC'16), Edinburgh, UK, pages 1271--1280, 1999.
23
24
25
26

Collaborative Colleagues:
Susanne Bürklen: colleagues
Pedro José Marrón: colleagues
Kurt Rothermel: colleagues
Timo Pfahl: colleagues