Fuzzy Logic-Based Cluster Heads Percentage Calculation for Improving the Performance of the LEACH Protocol

Banimelhem, Omar; Taqieddin, Eyad; Awad, Fahed; Mowafi, Moad; Al-Ma'aqbeh, Feda'

doi:10.4018/ijfsa.2015100106

“…In (Banimelhem et al, 2015) authors proposed a variant of well-known LEACH clustering protocol,namelyFL-LEACH.ThealgorithmofFL-LEACHisbasedondeterminingtheclusters numberusedbyLEACHviafuzzylogicdecision-makingscheme.Thisrelatestheclustersnumberto somecharacteristicsofthenetworklikethenumberofnodes,thesensingfield,andtheemplacement ofthesink.TheFL-LEACHperformsbetterthanLEACHprotocolintermsofnetworklifetimeand networkresidualenergy.ThedeficienciesofFL-LEACHencompass;unbalancedsizeofclusterand non-optimalnumberofCHs.…”

Section: Related Workmentioning

confidence: 99%

Fuzzy Logic Based Clustering Algorithm for Wireless Sensor Networks

Alami

¹

,

Najid

²

2017

International Journal of Fuzzy System Applications

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WSNs have many applications in modern life. Thus, optimization of the network operation is required to maximize its lifetime. The energy is a major issue in order to increase the lifetime of WSNs. The clustering algorithm is one of the proposed algorithms to enhance the lifetime of WSNs. The operation of the clustering algorithm is divided into cluster heads (CHs) selection and cluster formation. However, most of the previous works have focused on CHs selection, and have not considered the cluster formation process, which is the important issue in clustering algorithm based routing schemes, and it can drastically affect the lifetime of WSNs. In this paper, a Fuzzy Logic based Clustering Algorithm for WSN (CAFL) has been proposed to improve the lifetime of WSNs. This approach uses fuzzy logic for CHs selection and clusters formation processes by using residual energy and closeness to the sink as fuzzy inputs in terms of CH selection, and residual energy of CH and closeness to CHs as fuzzy inputs in terms of clusters formation. Simulation results justify its efficiency.

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“…[11][12][13] In the proposed cross-layer design, to improve the delay, data loss, and energy consumption, a fuzzy logic controller is employed to adapt the data rate, at the application layer, to the network conditions according to feedback information from the network and physical layers. The data rate is adjusted by dynamically changing the spatial resolution of the transmitted images.…”

Section: Introductionmentioning

confidence: 99%

Fuzzy Logic Based Cross-Layer Design for Image Transmission in Wireless Sensor Networks

Mowafi¹,

Banimelhem²,

Taher³

2018

IJCIS

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The evolution of wireless multimedia sensor networks (WMSN) has opened the door to a wide range of applications such as telemedicine, surveillance, and intrusion detection. However, the delivery of multimedia content over wireless sensor networks requires maintaining the quality of service demands of the applications as well as the resource constraints of the network. This has motivated the design of cross-layer architectures as a promising solution for efficiently meeting the quality of service requirements and the resource constraints in WMSN. In this paper, a cross-layer design for image transmission, using fuzzy logic, is proposed to provide quality of service guarantees and efficient resource utilization in WMSN. The proposed cross-layer design takes into consideration the trade-off between the network performance and the quality of received images by exploiting the information exchange between different layers in the protocol stack. The simulation results demonstrate that the proposed approach can efficiently improve the network performance in terms of packet loss, delay, and energy consumption, while maintaining an acceptable level of quality of the received images.

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Fuzzy Logic Based Clustering Algorithm for Wireless Sensor Networks

Alami

¹

,

Najid

²

2020

View full text Add to dashboard Cite

WSNs have many applications in modern life. Thus, optimization of the network operation is required to maximize its lifetime. The energy is a major issue in order to increase the lifetime of WSNs. The clustering algorithm is one of the proposed algorithms to enhance the lifetime of WSNs. The operation of the clustering algorithm is divided into cluster heads (CHs) selection and cluster formation. However, most of the previous works have focused on CHs selection, and have not considered the cluster formation process, which is the important issue in clustering algorithm based routing schemes, and it can drastically affect the lifetime of WSNs. In this paper, a Fuzzy Logic based Clustering Algorithm for WSN (CAFL) has been proposed to improve the lifetime of WSNs. This approach uses fuzzy logic for CHs selection and clusters formation processes by using residual energy and closeness to the sink as fuzzy inputs in terms of CH selection, and residual energy of CH and closeness to CHs as fuzzy inputs in terms of clusters formation. Simulation results justify its efficiency.

show abstract

Fuzzy Logic-Based Cluster Heads Percentage Calculation for Improving the Performance of the LEACH Protocol

Cited by 4 publications

References 30 publications

Fuzzy Logic Based Clustering Algorithm for Wireless Sensor Networks

Fuzzy Logic Based Clustering Algorithm for Wireless Sensor Networks

Fuzzy Logic Based Cross-Layer Design for Image Transmission in Wireless Sensor Networks

Fuzzy Logic Based Clustering Algorithm for Wireless Sensor Networks

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