Sustainability enhancement multihop clustering in cognitive radio sensor networks

Jong Hong Park; Yeonghun Nam; Jong Moon Chung

doi:10.1155/2015/574340

Sustainability enhancement multihop clustering in cognitive radio sensor networks

Jong Hong Park, Yeonghun Nam, Jong Moon Chung

Department of Electrical and Electronic Engineering

Research output: Contribution to journal › Article › peer-review

4 Citations (Scopus)

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	https://doi.org/10.1155/2015/574340
Publication status	Published - 2015

Bibliographical note

Publisher Copyright:
© 2015 Jong-Hong Park et al.

All Science Journal Classification (ASJC) codes

Engineering(all)
Computer Networks and Communications

UN SDGs

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

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10.1155/2015/574340

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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.",

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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.

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Sustainability enhancement multihop clustering in cognitive radio sensor networks

Abstract

Bibliographical note

All Science Journal Classification (ASJC) codes

UN SDGs

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