| |
| description |
The proliferation of mobile devices has led to the creation of
hoarding algorithms that attempt to mitigate the problems related
with disconnected operation or with the operation in areas where
bandwidth is either scarce or very expensive. Traditional hoarding
approaches use probability access tables to determine what
information needs to be sent to the mobile device, but fail to take
the structured nature of data into account. In this paper, we
present an enhanced hoarding approach for semistructured information
that relies on the analysis of graphs to determine the information
that needs to be hoarded. We show by means of experimental
evaluations on webpages that our approach outperforms other hoarding
algorithms that treat information as the combination of unrelated
items.
|
| publisher |
University of Stuttgart : Collaborative Research Center SFB 627
(Nexus: World Models for Mobile Context-Based
Systems)
|
| Los Alamitos: IEEE Computer Society
|
| type |
Text
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| Article in Proceedings
|
| source |
In: Proceedings of the 5th IEEE International Conference on Mobile
Data Management (MDM 2004); Berkeley, California, USA; January
19-22, 2004, pp. 1-1
|
| contributor |
Institut für Parallele und Verteilte Systeme, Verteilte
Systeme
|
|
| subject |
Information Storage and Retrieval Systems and Software (CR
H.3.4)
| | Pattern Recognition Clustering (CR I.5.3)
| | relation |
International Conference on Mobile Data Management
| |