Abstract
A cognitive radio based hybrid data-type clustering (CR-HDC) algorithm is proposed to maximize network energy efficiency of cognitive radio (CR) sensor networks (CRSNs). By analyzing the overall energy consumption of CRSNs under various conditions, the optimal transmission range of a sensor node can be obtained for both when spectrum handoff (SHO) is applied and when it is not. Simulation results show that CR-HDC achieves performance enhancements in terms of network lifetime and the number of packets received at the base station (BS) compared to when applying the centralized low energy adaptive clustering hierarchy (LEACH-C) or hybrid data-type clustering (HDC) to CRSN environments.
| Original language | English |
|---|---|
| Article number | 574340 |
| Journal | International Journal of Distributed Sensor Networks |
| Volume | 2015 |
| DOIs | |
| Publication status | Published - 2015 Jan 1 |
Fingerprint
All Science Journal Classification (ASJC) codes
- Engineering(all)
- Computer Networks and Communications
Cite this
}
Sustainability enhancement multihop clustering in cognitive radio sensor networks. / Park, Jong Hong; Nam, Yeonghun; Chung, Jong-Moon.
In: International Journal of Distributed Sensor Networks, Vol. 2015, 574340, 01.01.2015.Research output: Contribution to journal › Article
TY - JOUR
T1 - Sustainability enhancement multihop clustering in cognitive radio sensor networks
AU - Park, Jong Hong
AU - Nam, Yeonghun
AU - Chung, Jong-Moon
PY - 2015/1/1
Y1 - 2015/1/1
N2 - A cognitive radio based hybrid data-type clustering (CR-HDC) algorithm is proposed to maximize network energy efficiency of cognitive radio (CR) sensor networks (CRSNs). By analyzing the overall energy consumption of CRSNs under various conditions, the optimal transmission range of a sensor node can be obtained for both when spectrum handoff (SHO) is applied and when it is not. Simulation results show that CR-HDC achieves performance enhancements in terms of network lifetime and the number of packets received at the base station (BS) compared to when applying the centralized low energy adaptive clustering hierarchy (LEACH-C) or hybrid data-type clustering (HDC) to CRSN environments.
AB - A cognitive radio based hybrid data-type clustering (CR-HDC) algorithm is proposed to maximize network energy efficiency of cognitive radio (CR) sensor networks (CRSNs). By analyzing the overall energy consumption of CRSNs under various conditions, the optimal transmission range of a sensor node can be obtained for both when spectrum handoff (SHO) is applied and when it is not. Simulation results show that CR-HDC achieves performance enhancements in terms of network lifetime and the number of packets received at the base station (BS) compared to when applying the centralized low energy adaptive clustering hierarchy (LEACH-C) or hybrid data-type clustering (HDC) to CRSN environments.
UR - http://www.scopus.com/inward/record.url?scp=84947576216&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84947576216&partnerID=8YFLogxK
U2 - 10.1155/2015/574340
DO - 10.1155/2015/574340
M3 - Article
VL - 2015
JO - International Journal of Distributed Sensor Networks
JF - International Journal of Distributed Sensor Networks
SN - 1550-1329
M1 - 574340
ER -