Error resilient image transport in wireless sensor networks

In this paper, we propose an “in-network” diversity combining scheme for image transport over wireless sensor networks. We consider a wireless sensor network with both wireless link impairments and node failures. We analyze two performance metrics of the proposed image transport scheme: energy consu...

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Bibliographic Details
Published in:Computer networks (Amsterdam, Netherlands : 1999) Netherlands : 1999), 2006-10, Vol.50 (15), p.2873-2887
Main Authors: Wu, Huaming, Abouzeid, Alhussein A.
Format: Article
Language:English
Subjects:
Applied sciences
Diversity combining
Energy consumption
Equipments and installations
Error analysis
Error correction & detection
Exact sciences and technology
Forward error correction
Image transport
Markov analysis
Miscellaneous
Mobile communications
Mobile radiocommunication systems
Networks
Radiocommunications
Sensor networks
Sensors
Services and terminals of telecommunications
Studies
Systems, networks and services of telecommunications
Telecommunications
Telecommunications and information theory
Telemetry. Remote supervision. Telewarning. Remote control
Teleprocessing networks. Isdn
Transmission and modulation (techniques and equipments)
Wireless communications
Wireless networks
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Summary:In this paper, we propose an “in-network” diversity combining scheme for image transport over wireless sensor networks. We consider a wireless sensor network with both wireless link impairments and node failures. We analyze two performance metrics of the proposed image transport scheme: energy consumption and received image quality distortion. Our analysis models key aspects of the network including forward error correction, path diversity, and the multi-hop nature of ad-hoc networks. The channel model used is a two-state Markov model describing errors on the bit level. We also use a two-state Markov model of node transitions between an “on” and “off” state. Reed–Solomon coding is used for forward error correction. Theoretical and simulation results show the robustness improvement. This work also helps in understanding the tradeoffs between image quality distortion and energy consumption as a function of various network parameters such as the number of hops between the source and the destination, the average channel error rate, and the average node failure rate.
ISSN:1389-1286
1872-7069
DOI:10.1016/j.comnet.2005.09.039