Portfolio theory based sensor selection in Wireless Sensor Networks with unreliable observations

Nianxia Cao, Swastik Brahma, Pramod Kumar Varshney

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

1 Scopus citations

Abstract

In this paper, we propose a portfolio theory based sensor selection framework in Wireless Sensor Networks (WSNs) with unreliable sensor observations for target localization. Fisher information (FI) is used as the sensor selection metric in our work. Our objective is to find a sensor selection scheme that considers both the expected FI gain and the reliability of the sensors, where we observe that the FI variability captures the reliability of the sensors. Based on portfolio theory, we formulate our sensor selection problem as a multiobjective optimization problem (MOP), which is solved by the normal boundary intersection (NBI) method. Simulation results show the advantages of performing portfolio theory based sensor selection.

Original languageEnglish (US)
Title of host publication2016 50th Annual Conference on Information Systems and Sciences, CISS 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages454-459
Number of pages6
ISBN (Electronic)9781467394574
DOIs
StatePublished - Apr 26 2016
Event50th Annual Conference on Information Systems and Sciences, CISS 2016 - Princeton, United States
Duration: Mar 16 2016Mar 18 2016

Other

Other50th Annual Conference on Information Systems and Sciences, CISS 2016
CountryUnited States
CityPrinceton
Period3/16/163/18/16

Keywords

  • Diversification
  • Multiobjective optimization
  • Portfolio theory
  • Target localization

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Information Systems

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    Cao, N., Brahma, S., & Varshney, P. K. (2016). Portfolio theory based sensor selection in Wireless Sensor Networks with unreliable observations. In 2016 50th Annual Conference on Information Systems and Sciences, CISS 2016 (pp. 454-459). [7460545] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CISS.2016.7460545