Document Type

Conference Proceeding

Language

eng

Format of Original

6 p.

Publication Date

8-2011

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Source Publication

Fifth ACM/IEEE International Conference on Distributed Smart Cameras (ICDSC), August 22-25, 2011

Source ISSN

978-1-4577-1706-2

Abstract

Wireless sensor networks (WSN) typically employ dynamic duty cycle schemes to efficiently handle different patterns of communication traffic in the network. However, existing duty cycling approaches are not suitable for event-driven WSN, in particular, camera-based networks designed to track humans and objects. A characteristic feature of such networks is the spatially-correlated bursty traffic that occurs in the vicinity of potentially highly mobile objects. In this paper, we propose a concept of indirect sensing in the MAC layer of a wireless camera network and an active duty cycle adaptation scheme based on Kalman filter that continuously predicts and updates the location of the object that triggers bursty communication traffic in the network. This prediction allows the camera nodes to alter their communication protocol parameters prior to the actual increase in the communication traffic. Our simulations demonstrate that our active adaptation strategy outperforms TMAC not only in terms of energy efficiency and communication latency, but also in terms of TIBPEA, a QoS metric for event-driven WSN.

Comments

Accepted version. Published as part of the proceedings of the conference, Fifth ACM/IEEE International Conference on Distributed Smart Cameras (ICDSC), August 22-25, 2011. DOI.© 2011 IEEE. Reprinted, with permission, from Shin, P. J., Medeiros, H., Park, J., Kak, A. "Predictive duty cycle adaptation for wireless camera networks ". Fifth ACM/IEEE International Conference on Distributed Smart Cameras (ICDSC), August 2011. This material is posted here with permission of the IEEE. Such permission of the IEEE does not in any way imply IEEE endorsement of any of Marquette University’s products or services. Internal or personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution must be obtained from the IEEE by writing to pubs-permissions@ieee.org. By choosing to view this document, you agree to all provisions of the copyright laws protecting it.

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