An energy-driven adaptive cluster-head rotation algorithm for cognitive radio network

Guisen Xu; Xuezhi Tan; Shouming Wei; Shizeng Guo; Bin Wang

doi:10.1109/PCSPA.2010.42

An energy-driven adaptive cluster-head rotation algorithm for cognitive radio network

Guisen Xu^*
, Xuezhi Tan
, Shouming Wei
, Shizeng Guo
, Bin Wang

^*Corresponding author for this work

School of Electronics and Information Engineering

Harbin Institute of Technology

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

7 Scopus citations

Abstract

Cluster-based topology is an energy-efficient topology control method in cognitive radio networks. The cluster-head node depletes energy faster than cluster-member node and the rotation of cluster-head node is needed to balance the energy consumption for the whole network. In this paper, EDCRN (Energy-Driven Cognitive Radio Network) is presented, which rotation energy threshold is estimated using cluster-head node real-time energy load. The simulation result show that comparing with LEACH (Low-Energy Adaptive Clustering Hierarchy) and EDAC, EDCRN can realize the more network lifetime than the others.

Original language	English
Title of host publication	Proceedings - 2010 1st International Conference on Pervasive Computing, Signal Processing and Applications, PCSPA 2010
Pages	138-141
Number of pages	4
DOIs	https://doi.org/10.1109/PCSPA.2010.42
State	Published - 2010
Event	1st International Conference on Pervasive Computing, Signal Processing and Applications, PCSPA 2010 - Harbin, China Duration: 17 Sep 2010 → 19 Sep 2010

Publication series

Name	Proceedings - 2010 1st International Conference on Pervasive Computing, Signal Processing and Applications, PCSPA 2010

Conference

Conference	1st International Conference on Pervasive Computing, Signal Processing and Applications, PCSPA 2010
Country/Territory	China
City	Harbin
Period	17/09/10 → 19/09/10

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 7 Affordable and Clean Energy

Keywords

Clustering
Cognitive radio network
Energy-Driven
Rotating

Access to Document

10.1109/PCSPA.2010.42

Cite this

Xu, G., Tan, X., Wei, S., Guo, S., & Wang, B. (2010). An energy-driven adaptive cluster-head rotation algorithm for cognitive radio network. In Proceedings - 2010 1st International Conference on Pervasive Computing, Signal Processing and Applications, PCSPA 2010 (pp. 138-141). Article 5635692 (Proceedings - 2010 1st International Conference on Pervasive Computing, Signal Processing and Applications, PCSPA 2010). https://doi.org/10.1109/PCSPA.2010.42

Xu, Guisen ; Tan, Xuezhi ; Wei, Shouming et al. / An energy-driven adaptive cluster-head rotation algorithm for cognitive radio network. Proceedings - 2010 1st International Conference on Pervasive Computing, Signal Processing and Applications, PCSPA 2010. 2010. pp. 138-141 (Proceedings - 2010 1st International Conference on Pervasive Computing, Signal Processing and Applications, PCSPA 2010).

@inproceedings{b6cdf93ff1b646ffbf2bf53e1de515af,

title = "An energy-driven adaptive cluster-head rotation algorithm for cognitive radio network",

abstract = "Cluster-based topology is an energy-efficient topology control method in cognitive radio networks. The cluster-head node depletes energy faster than cluster-member node and the rotation of cluster-head node is needed to balance the energy consumption for the whole network. In this paper, EDCRN (Energy-Driven Cognitive Radio Network) is presented, which rotation energy threshold is estimated using cluster-head node real-time energy load. The simulation result show that comparing with LEACH (Low-Energy Adaptive Clustering Hierarchy) and EDAC, EDCRN can realize the more network lifetime than the others.",

keywords = "Clustering, Cognitive radio network, Energy-Driven, Rotating",

author = "Guisen Xu and Xuezhi Tan and Shouming Wei and Shizeng Guo and Bin Wang",

year = "2010",

doi = "10.1109/PCSPA.2010.42",

language = "英语",

isbn = "9780769541808",

series = "Proceedings - 2010 1st International Conference on Pervasive Computing, Signal Processing and Applications, PCSPA 2010",

pages = "138--141",

booktitle = "Proceedings - 2010 1st International Conference on Pervasive Computing, Signal Processing and Applications, PCSPA 2010",

note = "1st International Conference on Pervasive Computing, Signal Processing and Applications, PCSPA 2010 ; Conference date: 17-09-2010 Through 19-09-2010",

}

Xu, G, Tan, X, Wei, S , Guo, S & Wang, B 2010, An energy-driven adaptive cluster-head rotation algorithm for cognitive radio network. in Proceedings - 2010 1st International Conference on Pervasive Computing, Signal Processing and Applications, PCSPA 2010., 5635692, Proceedings - 2010 1st International Conference on Pervasive Computing, Signal Processing and Applications, PCSPA 2010, pp. 138-141, 1st International Conference on Pervasive Computing, Signal Processing and Applications, PCSPA 2010, Harbin, China, 17/09/10. https://doi.org/10.1109/PCSPA.2010.42

An energy-driven adaptive cluster-head rotation algorithm for cognitive radio network. / Xu, Guisen; Tan, Xuezhi; Wei, Shouming et al.
Proceedings - 2010 1st International Conference on Pervasive Computing, Signal Processing and Applications, PCSPA 2010. 2010. p. 138-141 5635692 (Proceedings - 2010 1st International Conference on Pervasive Computing, Signal Processing and Applications, PCSPA 2010).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - An energy-driven adaptive cluster-head rotation algorithm for cognitive radio network

AU - Xu, Guisen

AU - Tan, Xuezhi

AU - Wei, Shouming

AU - Guo, Shizeng

AU - Wang, Bin

PY - 2010

Y1 - 2010

N2 - Cluster-based topology is an energy-efficient topology control method in cognitive radio networks. The cluster-head node depletes energy faster than cluster-member node and the rotation of cluster-head node is needed to balance the energy consumption for the whole network. In this paper, EDCRN (Energy-Driven Cognitive Radio Network) is presented, which rotation energy threshold is estimated using cluster-head node real-time energy load. The simulation result show that comparing with LEACH (Low-Energy Adaptive Clustering Hierarchy) and EDAC, EDCRN can realize the more network lifetime than the others.

AB - Cluster-based topology is an energy-efficient topology control method in cognitive radio networks. The cluster-head node depletes energy faster than cluster-member node and the rotation of cluster-head node is needed to balance the energy consumption for the whole network. In this paper, EDCRN (Energy-Driven Cognitive Radio Network) is presented, which rotation energy threshold is estimated using cluster-head node real-time energy load. The simulation result show that comparing with LEACH (Low-Energy Adaptive Clustering Hierarchy) and EDAC, EDCRN can realize the more network lifetime than the others.

KW - Clustering

KW - Cognitive radio network

KW - Energy-Driven

KW - Rotating

UR - https://www.scopus.com/pages/publications/78650501363

U2 - 10.1109/PCSPA.2010.42

DO - 10.1109/PCSPA.2010.42

M3 - 会议稿件

AN - SCOPUS:78650501363

SN - 9780769541808

T3 - Proceedings - 2010 1st International Conference on Pervasive Computing, Signal Processing and Applications, PCSPA 2010

SP - 138

EP - 141

BT - Proceedings - 2010 1st International Conference on Pervasive Computing, Signal Processing and Applications, PCSPA 2010

T2 - 1st International Conference on Pervasive Computing, Signal Processing and Applications, PCSPA 2010

Y2 - 17 September 2010 through 19 September 2010

ER -

Xu G, Tan X, Wei S , Guo S, Wang B. An energy-driven adaptive cluster-head rotation algorithm for cognitive radio network. In Proceedings - 2010 1st International Conference on Pervasive Computing, Signal Processing and Applications, PCSPA 2010. 2010. p. 138-141. 5635692. (Proceedings - 2010 1st International Conference on Pervasive Computing, Signal Processing and Applications, PCSPA 2010). doi: 10.1109/PCSPA.2010.42

An energy-driven adaptive cluster-head rotation algorithm for cognitive radio network

Abstract

Publication series

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UN SDGs

Keywords

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