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Collaboration framework for data compensation in sensor networks

Authors: Pierre F. Tiako; Le Gruenwald;

Collaboration framework for data compensation in sensor networks

Abstract

This paper proposes a new approach of modeling the collaboration of sensor system artifacts to address the security and survivability concerns of sensor networks. The model considered is composed of sensors, base and users. Sensors are nodes that acquire and process data. Base is the node that acquires and processes data from sensors and provides an interface to access and monitor the sensor network while users monitor the system. The model proposed is instantiated and validated using association rule mining to compensate missing data in order to provide security and survivability to sensor networks.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
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