Abstract
Wireless sensor nodes typically have limited processing capabilities and are powered by batteries. the amount of energy expended in transmitting a single data bit would be several orders of magnitude higher when compared to the energy needed for a 32-bit computation. Thus, to maximize network lifetime, data transmissions should be minimized without losing vital information. in this paper, a novel adaptive compression scheme using nonlinear estimation theory is proposed for data aggregation. Satisfactory performance of the proposed compression scheme in the presence of noise, distortion, and quantization errors is demonstrated using Lyapunov approach. the proposed scheme is contrasted with existing compression schemes using various metrics applicable to wireless sensor networks such as energy efficiency, distortion and compression ratio. Simulation and hardware experimental results demonstrate almost 50% energy savings with very low distortion (less than 5%) and overhead. by iteratively applying the proposed scheme at the cluster head nodes, higher energy savings are obtained with a tolerable level of distortion. ©2010 IEEE.
Recommended Citation
P. Kasirajan et al., "A New Adaptive Compression Scheme for Data Aggregation in Wireless Sensor Networks," IEEE Wireless Communications and Networking Conference, WCNC, article no. 5506541, Institute of Electrical and Electronics Engineers, Aug 2010.
The definitive version is available at https://doi.org/10.1109/WCNC.2010.5506541
Department(s)
Electrical and Computer Engineering
Second Department
Computer Science
Keywords and Phrases
Compression; Data aggregation; Distortion; Energy efficiency; Wireless sensor networks
International Standard Book Number (ISBN)
978-142446398-5
International Standard Serial Number (ISSN)
1525-3511
Document Type
Article - Conference proceedings
Document Version
Citation
File Type
text
Language(s)
English
Rights
© 2024 Institute of Electrical and Electronics Engineers, All rights reserved.
Publication Date
03 Aug 2010
