MidFusion: An adaptive middleware for information fusion in sensor network applications

  • Authors:

  • Hitha Alex;Mohan Kumar;Behrooz Shirazi

  • Affiliations:

  • Department of Computer Science and Engineering, University of Texas at Arlington, P.O. Box 19015, 416 Yates Street, Arlington, TX 76019-0015, United States;Department of Computer Science and Engineering, University of Texas at Arlington, P.O. Box 19015, 416 Yates Street, Arlington, TX 76019-0015, United States;Department of Computer Science and Engineering, University of Texas at Arlington, P.O. Box 19015, 416 Yates Street, Arlington, TX 76019-0015, United States

  • Venue:
  • Information Fusion
  • Year:
  • 2008

Quantified Score

Hi-index 0.00

Visualization

Abstract

Applications and services are increasingly dependent on networks of smart sensors embedded in the environment to constantly sense and react to events. In a typical sensor network application, information is collected from a large number of distributed and heterogeneous sensor nodes. Information fusion in such applications is a challenging research issue due to the dynamicity, heterogeneity, and resource limitations of sensor networks. We present MidFusion, an adaptive middleware architecture to facilitate information fusion in sensor network applications. MidFusion discovers and selects the best set of sensors or sensor agents on behalf of applications (transparently), depending on the quality of service (QoS) guarantees and the cost of information acquisition. We also provide the theoretical foundation for MidFusion to select the best set of sensors using the principles of Bayesian and Decision theories. A sensor selection algorithm (SSA) for selecting the best set of sensors is presented in this paper. Our theoretical findings are validated through simulation of the SSA algorithm on an example scenario.