On sensor selection in linked information networks

Charu C. Aggarwal, Amotz Bar-Noy, Simon Shamoun

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

16 Scopus citations

Abstract

Sensor networks are often redundant by design in order to achieve reliability in information processing. In many cases, the relationships between the different sensors are known a-priori, and can be represented as virtual linkages among the different sensors. These virtual linkages correspond to an information network of sensors, which provides useful external input to the problem of sensor selection. In this paper, we propose the unique approach of using external linkage information in order to improve the efficiency of very large scale sensor selection. We design efficient theoretical models, including a greedy approximation algorithm and an integer programming formulation for sensor selection. Our greedy selection algorithm provides an approximation bound of (ℓ 1)/(2 ℓ 1), where e is the base of the natural logarithm. We show that our approach is much more effective than baseline sampling strategies. We present experimental results that illustrate the effectiveness and efficiency of our approach.

Original languageEnglish
Title of host publication2011 International Conference on Distributed Computing in Sensor Systems and Workshops, DCOSS'11
DOIs
StatePublished - 2011
Externally publishedYes
Event7th IEEE International Conference on Distributed Computing in Sensor Systems, DCOSS'11 - Barcelona, Spain
Duration: 27 Jun 201129 Jun 2011

Publication series

Name2011 International Conference on Distributed Computing in Sensor Systems and Workshops, DCOSS'11

Conference

Conference7th IEEE International Conference on Distributed Computing in Sensor Systems, DCOSS'11
Country/TerritorySpain
CityBarcelona
Period27/06/1129/06/11

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