PC3: principal component-based context compression

Anagnostopoulos, C. , Hadjiefthymiades, S. and Georgas, P. (2012) PC3: principal component-based context compression. Journal of Parallel and Distributed Computing, 72(2), pp. 155-170. (doi: 10.1016/j.jpdc.2011.10.001)

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We focus on energy efficiency, which guarantees the operation of a Wireless Sensor Network for long. We propose a context compression model that works in an orthogonal fashion. We first reduce the dimensions of multivariate contextual information. This is achieved through the Principal Component Analysis (PCA), which determines the statistical dependencies between the different contextual components. We then suppress the transmission of the determined principal components through an extrapolation scheme that exploits the properties of each individual component. Our findings are quite promising for the broader domain of WSN-based application engineering and context awareness.

Item Type:Articles
Glasgow Author(s) Enlighten ID:Anagnostopoulos, Dr Christos
Authors: Anagnostopoulos, C., Hadjiefthymiades, S., and Georgas, P.
College/School:College of Science and Engineering > School of Computing Science
Journal Name:Journal of Parallel and Distributed Computing
ISSN (Online):1096-0848

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