An adaptive epidemic information dissemination model for wireless sensor networks

Anagnostopoulos, C., Sekkas, O. and Hadjiefthymiades, S. (2012) An adaptive epidemic information dissemination model for wireless sensor networks. Pervasive and Mobile Computing, 8(5), pp. 751-763. (doi:10.1016/j.pmcj.2011.06.005)

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A major issue in Wireless Sensor Networks (WSN) is the efficient dissemination of data from sources to the entire network. A WSN node adopts some data dissemination algorithm for diffusing information in the network, e.g., flooding, bio-inspired spreading and gossipping [1]. The main objective of such algorithms is to reliably spread information across a WSN where no direct path from source to (any) destination can be secured. We focus on a specific bio-inspired dissemination algorithm: the epidemic algorithm [2]. Such algorithm (along with its variants and extensions) has been widely used for data dissemination in WSNs because of its reliability and spreading efficiency [3], [4] and [5]. Most epidemic-based algorithms take into account the characteristics of the nodes and the network for diffusing information. However, the characteristics of the disseminated data can be also taken into consideration for increasing the dissemination efficiency. In this paper, we introduce a data-centric, adaptive epidemic algorithm which takes into account statistical features of the disseminated data. The proposed algorithm extends the basic epidemic algorithm by adapting key operational parameters like the forwarding probability and validity period. Such adaptation results to a more efficient scheme than the conventional (probabilistic) epidemic algorithms.

Item Type:Articles
Glasgow Author(s) Enlighten ID:Anagnostopoulos, Dr Christos
Authors: Anagnostopoulos, C., Sekkas, O., and Hadjiefthymiades, S.
College/School:College of Science and Engineering > School of Computing Science
Journal Name:Pervasive and Mobile Computing
ISSN (Online):1873-1589

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