An adaptive epidemic information dissemination model for wireless sensor networks

Authors:
Christos Anagnostopoulos;Odysseas Sekkas;Stathes Hadjiefthymiades
Affiliations:
Department of Informatics, Ionian University, Corfu, Greece;Department of Informatics and Telecommunications, University of Athens, Greece;Department of Informatics and Telecommunications, University of Athens, Greece
Venue:
Pervasive and Mobile Computing
Year:
2012

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Abstract

We propose an adaptive bio-inspired information dissemination model that exploits the specific characteristics of the sampled/generated data stream (DS) in a wireless sensor network. Our model extends the basic epidemic algorithm by adapting key operational parameters (i.e., the forwarding probability and validity period) of the data dissemination process. The main idea is that the forwarding probability is tuned according to the variability of the involved DS. Our findings from the introduction of this adaptive epidemic are quite promising. Our scheme supersedes conventional probabilistic information dissemination algorithms in terms of efficiency and reliability.