Selecting reliable sensors via convex optimization

Vasileios Kekatos, Georgios B Giannakis

Research output: Chapter in Book/Report/Conference proceedingConference contribution

6 Scopus citations

Abstract

One of the key challenges in sensor networks is the extraction of trusted and relevant information by fusing data from a multitude of heterogeneous, distinct, but possibly unreliable or irrelevant sensors. Recovering the desirable view of the environment from the maximum number of dependable sensors while specifying the unreliable ones is an issue of paramount importance for active sensing and robust operation of the entire network. This problem of robust sensing is formulated here, and proved to be NP-hard. In the quest of sub-optimum but practically feasible solutions with quantifiable performance guarantees, two algorithms are developed for selecting reliable sensors via convex programming. The first relies on a convex relaxation of the original problem, while the second one is based on approximating the initial objective function by a concave one. Their performance is tested analytically, and through simulations.

Original languageEnglish (US)
Title of host publication2010 IEEE 11th International Workshop on Signal Processing Advances in Wireless Communications, SPAWC 2010
DOIs
StatePublished - Dec 1 2010
Event2010 IEEE 11th International Workshop on Signal Processing Advances in Wireless Communications, SPAWC 2010 - Marrakech, Morocco
Duration: Jun 20 2010Jun 23 2010

Publication series

NameIEEE Workshop on Signal Processing Advances in Wireless Communications, SPAWC

Other

Other2010 IEEE 11th International Workshop on Signal Processing Advances in Wireless Communications, SPAWC 2010
Country/TerritoryMorocco
CityMarrakech
Period6/20/106/23/10

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