Spectrum aware fuzzy clustering algorithm for cognative radio sensor networks

Noor, Norhazilan Md; Din, Norashidah Md

doi:10.4314/jfas.v9i4s.21

Cited by 2 publications

(4 citation statements)

References 15 publications

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“…The nodes have 0.5 J battery power. The performance of the proposed algorithm is compared with LEACH [16], SAFCA [15] and CogLEACH [4].…”

Section: Resultsmentioning

confidence: 99%

“…The fuzzy technique can reduce the computation overhead [14] a contributing factor to a resource and spectrum constraint CRSN. The work of this paper is a continuation of the CH election engaged in [15]] and therefore, the focus in this paper is mainly on the cluster formation algorithm. Unlike the physical proximity and common channel utilized in the existing CRSN clustering algorithm, the CH residual energy and relative channel availability are exploited in this paper.…”

Section: Introductionmentioning

confidence: 99%

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Spectrum Aware Cluster Formation Scheme for Cognitive Radio Sensor Network

Noor

Din

Kasiran³

2018

IJET

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In Cognitive Radio Sensor Network (CRSN), a cognitive radio sensor node operated on a dynamic spectrum allocation with limited computational and energy resource. A cognitive radio sensor node must vacate an occupied channel degrading its performance due to reclustering as the common channel no longer available. Furthermore, energy is mostly consumed during data transmission mechanism. Clustering is the best architecture model to minimize energy consumption among the nodes. With the objective of a robust cluster while maximizing network lifetime, a fuzzy logic technique is proposed. A metric named relative common channel is also proposed. The fuzzy logic combines two input parameters, the relative common channel and residual energy to elect the best suitable cluster head to minimize reclustering and maximize the network lifetime. The performance of the proposed algorithm is compared with LEACH, SAFCA and CogLEACH. The results show that the CRSN has more extended network lifetime and more balanced energy consumption attributed to the robust cluster formation.

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“…The nodes have 0.5 J battery power. The performance of the proposed algorithm is compared with LEACH [16], SAFCA [15] and CogLEACH [4].…”

Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Spectrum Aware Cluster Formation Scheme for Cognitive Radio Sensor Network

Noor

Din

Kasiran³

2018

IJET

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“…The integration of the two technologies, the Cognitive Radio Sensor Network (CRSN) offers the WSN to opportunistically dynamic access in the licensed bands (Peng et al, 2010). A new WSN protocol design that address the combination of both technologies is essential due to its unique characteristic and common attributes to the traditional WSN (Noor & Din, 2017).…”

Section: Introductionmentioning

confidence: 99%

“…The fuzzy logic technique delivers its output without a complex mathematical model (Rauniyar & Shin, 2015). It rules based decision reduces the processing overhead (Noor & Din, 2017). The fuzzy logic can overcome the various uncertainties in clustering process (Bagci & Yazici, 2013) unlike the weight based which rely on the exact value.…”

Section: Introductionmentioning

confidence: 99%

Spectrum Aware Clustering Algorithm Based on Fuzzy Logic for Cognitive Radio Sensor Network

Noor

Din

Abdullah

et al. 2020

MJoC

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In this paper, a clustering solution for periodic data gathering over WSNs using cognitive radio technology is proposed. The cluster heads (CHs) are selected according to the channel availability, residual energy, communication cost and node distribution parameters. Fuzzy logic and weight based techniques combines the four parameters for the CH selection. The cluster formation is based on the relative channel availability between the cluster member (CM) and CH to ensure stable cluster connectivity from link failure. To evaluate the proposed clustering algorithm, the performance of sensor networks is compared with CogLEACH, LEACH and CHEF routing protocols. The simulation results show that the proposed clustering algorithm effectively has a significant improvement with respect to the network stability without reducing the network instability and network lifetime. In addition, the proposed clustering solution also has a low and almost consistent CH energy consumption during the stability period indicating an efficient cluster formation.

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Spectrum aware fuzzy clustering algorithm for cognative radio sensor networks

Cited by 2 publications

References 15 publications

Spectrum Aware Cluster Formation Scheme for Cognitive Radio Sensor Network

Spectrum Aware Cluster Formation Scheme for Cognitive Radio Sensor Network

Spectrum Aware Clustering Algorithm Based on Fuzzy Logic for Cognitive Radio Sensor Network

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