A Codebook-based Redundancy Suppression Mechanism with Lifetime Prediction in Cluster-based WSN
Wireless Sensor Network (WSN) comprises of sensor
nodes which are designed to sense the environment, transmit sensed
data back to the base station via multi-hop routing to reconstruct
physical phenomena. Since physical phenomena exists significant
overlaps between temporal redundancy and spatial redundancy, it is
necessary to use Redundancy Suppression Algorithms (RSA) for sensor
node to lower energy consumption by reducing the transmission
of redundancy. A conventional algorithm of RSAs is threshold-based
RSA, which sets threshold to suppress redundant data. Although
many temporal and spatial RSAs are proposed, temporal-spatial RSA
are seldom to be proposed because it is difficult to determine when
to utilize temporal or spatial RSAs. In this paper, we proposed a
novel temporal-spatial redundancy suppression algorithm, Codebookbase
Redundancy Suppression Mechanism (CRSM). CRSM adopts
vector quantization to generate a codebook, which is easily used to
implement temporal-spatial RSA. CRSM not only achieves power
saving and reliability for WSN, but also provides the predictability
of network lifetime. Simulation result shows that the network lifetime
of CRSM outperforms at least 23% of that of other RSAs.
[1] P. Juang et al., Energy-efficient computing for wildlife tracking: design
tradeoffs and early experiences with zebranet, In Proceedings of ASPLOS,
Oct. 2002.
[2] A. Mainwaring and J. Polastre and R. Szewczyk and D. Culler and J. Anderson,
Wireless sensor networks for habitat monitoring, In Proceedings
of WSNA, Sep. 2002.
[3] Wendi B. Heinzelman and Anantha P.Chandrakasan and HariBalakrishnan,
An application-specific protocol architecture for wireless microsensor
networks, T-COMM, vol. 1, no. 4, pp. 660-670, Oct. 2002.
[4] A. Manjeshwar and D. P. Agrawal, TEEN : A protocol for enhanced
efficiency in wireless sensor networks, 1st International Workshop on
Parallel and Distributed Computing Issues in Wireless Networks and
Mobile Computing, April 2001.
[5] Yunhao Liu and Mo Li, Iso-map: Energy-efficient contour mapping in
wireless sensor networks, IEEE ICDCS, June 2007.
[6] X. Meng and L. Li and T. Nandagopal and S. Lu., Contour maps:
Monitoring and diagnosis in sensor networks, Computer Networks, 2006.
[7] I. Koutsopoulos and S. Toumpis and L. Tassiulas, On the relation between
source and channel coding and sensor network deployment, International
Workshop on Wireless Ad-hoc networks (IWWAN) 2005, London UK.
[1] P. Juang et al., Energy-efficient computing for wildlife tracking: design
tradeoffs and early experiences with zebranet, In Proceedings of ASPLOS,
Oct. 2002.
[2] A. Mainwaring and J. Polastre and R. Szewczyk and D. Culler and J. Anderson,
Wireless sensor networks for habitat monitoring, In Proceedings
of WSNA, Sep. 2002.
[3] Wendi B. Heinzelman and Anantha P.Chandrakasan and HariBalakrishnan,
An application-specific protocol architecture for wireless microsensor
networks, T-COMM, vol. 1, no. 4, pp. 660-670, Oct. 2002.
[4] A. Manjeshwar and D. P. Agrawal, TEEN : A protocol for enhanced
efficiency in wireless sensor networks, 1st International Workshop on
Parallel and Distributed Computing Issues in Wireless Networks and
Mobile Computing, April 2001.
[5] Yunhao Liu and Mo Li, Iso-map: Energy-efficient contour mapping in
wireless sensor networks, IEEE ICDCS, June 2007.
[6] X. Meng and L. Li and T. Nandagopal and S. Lu., Contour maps:
Monitoring and diagnosis in sensor networks, Computer Networks, 2006.
[7] I. Koutsopoulos and S. Toumpis and L. Tassiulas, On the relation between
source and channel coding and sensor network deployment, International
Workshop on Wireless Ad-hoc networks (IWWAN) 2005, London UK.
@article{"International Journal of Electrical, Electronic and Communication Sciences:63135", author = "Huan Chen and Bo-Chao Cheng and Chih-Chuan Cheng and Yi-Geng Chen and Yu Ling Chou", title = "A Codebook-based Redundancy Suppression Mechanism with Lifetime Prediction in Cluster-based WSN", abstract = "Wireless Sensor Network (WSN) comprises of sensor
nodes which are designed to sense the environment, transmit sensed
data back to the base station via multi-hop routing to reconstruct
physical phenomena. Since physical phenomena exists significant
overlaps between temporal redundancy and spatial redundancy, it is
necessary to use Redundancy Suppression Algorithms (RSA) for sensor
node to lower energy consumption by reducing the transmission
of redundancy. A conventional algorithm of RSAs is threshold-based
RSA, which sets threshold to suppress redundant data. Although
many temporal and spatial RSAs are proposed, temporal-spatial RSA
are seldom to be proposed because it is difficult to determine when
to utilize temporal or spatial RSAs. In this paper, we proposed a
novel temporal-spatial redundancy suppression algorithm, Codebookbase
Redundancy Suppression Mechanism (CRSM). CRSM adopts
vector quantization to generate a codebook, which is easily used to
implement temporal-spatial RSA. CRSM not only achieves power
saving and reliability for WSN, but also provides the predictability
of network lifetime. Simulation result shows that the network lifetime
of CRSM outperforms at least 23% of that of other RSAs.", keywords = "Redundancy Suppression Algorithm (RSA),
Threshold-based RSA, Temporal RSA, Spatial RSA and Codebookbase
Redundancy Suppression Mechanism (CRSM)", volume = "3", number = "8", pages = "1640-5", }