Paper
15 February 2012 On the use of clustering for resource allocation in wireless visual sensor networks
Angeliki V. Katsenou, Lisimachos P. Kondi, Konstantinos E. Parsopoulos
Author Affiliations +
Proceedings Volume 8305, Visual Information Processing and Communication III; 83050S (2012) https://doi.org/10.1117/12.908743
Event: IS&T/SPIE Electronic Imaging, 2012, Burlingame, California, United States
Abstract
The present study is focused on the problem of quality-driven cross-layer optimization of Direct Sequence Code Division Multiple Access (DS-CDMA) Wireless Visual Sensor Networks (WVSNs). We consider a centralized topology where each sensor transmits directly to a Centralized Control Unit (CCU), which manages the network resources. In real environments, the visual sensors view and transmit scenes with varying amount of motion. Thus, each recorded video has its individual motion characteristics. Our aim is to enable the CCU to jointly allocate the transmission power and source-channel coding rates for each WVSN node under certain quality- driven criteria and constant chip rate. We consider two approaches for the cross-layer optimization scheme. In the first, the optimal set of network resources is assigned to each node according to its individual motion characteristics. In the second approach, the nodes are partitioned into clusters according to the amount of motion in the recorded scenes. Then, all nodes within a cluster are assigned identical network resources. Both approaches result in mixed-integer optimization problems, which are solved with the Particle Swarm Optimization algorithm. Experimental results demonstrate the quality/complexity trade-off for the two approaches.
© (2012) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Angeliki V. Katsenou, Lisimachos P. Kondi, and Konstantinos E. Parsopoulos "On the use of clustering for resource allocation in wireless visual sensor networks", Proc. SPIE 8305, Visual Information Processing and Communication III, 83050S (15 February 2012); https://doi.org/10.1117/12.908743
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Cited by 3 scholarly publications.
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KEYWORDS
Video

Distortion

Visualization

Particle swarm optimization

Forward error correction

Particles

Sensors

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