Fuzzy Based BEENISH Protocol for Wireless Sensor Network

Devasena, A.; Sowmya, B.

doi:10.4236/cs.2016.78164

Cited by 3 publications

(3 citation statements)

References 11 publications

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“…In Izadi et al (2013, 2015), the authors have addressed the issue of CH failure and presented an alternative clustering scheme in WSN. Alami and Najid (2016) and Devasena and Sowmya (2016) improve network lifetime by exploiting heterogeneity using fuzzy logic. Nayak and Devulapalli (2016) extend the concept of a two-tier LEACH technique using fuzzy logic by selecting a super CH among the selected CHs which collect data from other CHs and send to the BS.…”

Section: Introductionmentioning

confidence: 99%

A comprehensive review of fuzzy-based clustering techniques in wireless sensor networks

Singh

Soni

2017

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Purpose This paper aims to discuss a comprehensive survey on fuzzy-based clustering techniques. The determination of an appropriate sensor node as a cluster head straightforwardly affects a network’s lifetime. Clustering often possesses some uncertainties in determining suitable sensor nodes as a cluster head. Owing to various variables, selection of a suitable node as a cluster head is a perplexing decision. Fuzzy logic is capable of handling uncertainties and improving decision-making processes even with insufficient information. Then, state-of-the-art research in the field of clustering techniques has been reviewed. Design/methodology/approach The literature is presented in a tabular form with merits and limitations of each technique. Furthermore, the various techniques are compared graphically and classified in a tabular form and the flowcharts of important algorithms are presented with pseudocodes. Findings This paper comprehends the importance and distinction of different fuzzy-based clustering methods which are further supportive in designing more efficient clustering protocols. Originality/value This paper fulfills the need of a review paper in the field of fuzzy-based clustering techniques because no other paper has reviewed all the fuzzy-based clustering techniques. Furthermore, none of them has presented literature in a tabular form or presented flowcharts with pseudocodes of important techniques.

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Section: Introductionmentioning

confidence: 99%

A comprehensive review of fuzzy-based clustering techniques in wireless sensor networks

Singh

Soni

2017

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“…In [18] again authors have presented backup www.ijacsa.thesai.org cluster head concept with an improved algorithm using the type-2 fuzzy logic system. In [19] authors deployed sensors with different battery power and improved network lifetime by exploiting heterogeneity. The whole network is divided into circular disks based on the distance from the BS and further disks are segregated into clusters in [20].…”

Section: Related Workmentioning

confidence: 99%

“…The cluster head failure issue has been addressed in [17], [18] and introduced the backup cluster heads (BCHs) concept based upon fuzzy logic output value. The heterogeneity in the network is exploited using fuzzy logic in [19]. The segregation of network into tiers based on distance has been done in [20].…”

Section: Introductionmentioning

confidence: 99%

Uniform Segregation of Densely Deployed Wireless Sensor Networks

Singh¹,

Soni²

2017

ijacsa

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Abstract-In wireless sensor networks, the selection of cluster heads relies upon the various selection parameters, such as energy, distance, node concentration and rate of retransmission. There is always uncertainty in the suitability of sensor node for the cluster head role due to these various selection parameters. Fuzzy logic is capable of overcoming uncertainties even with incomplete available information. This quality of fuzzy logic can reduce uncertainty in cluster head selection up to large extent. Therefore, in this paper, a fuzzy logic based clustering approach is proposed to enhance the network operational lifetime. The cluster formation is done on the basis of the spatial correlation value between sensors to organize clusters uniformly in the network. The results are compared with well-known approaches CHEF and LEACH.

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Enhanced the Stability and Network Lift Time of Heterogeneous WSN Protocols

Yaduvanshi

Mishra

2022

IJARSCT

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In this research work we simulate all four protocols in MATLAB software DEEC, Developed-DEEC, Enhanced-DEEC, and I-BEENISH Protocol. we implement improved advanced fuzzy logic concept in I-BEENISH Protocol we compare the living nodes during rounds, nodes died during rounds, packets send to the base station and the size of CH of in all four protocols we compare the result simulations in result shows that I-BEENISH is more efficient compared to DEEC, Developed-DEEC and Enhanced-DEEC in conditions of network life-time and stability.

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Fuzzy Based BEENISH Protocol for Wireless Sensor Network

Cited by 3 publications

References 11 publications

A comprehensive review of fuzzy-based clustering techniques in wireless sensor networks

A comprehensive review of fuzzy-based clustering techniques in wireless sensor networks

Uniform Segregation of Densely Deployed Wireless Sensor Networks

Enhanced the Stability and Network Lift Time of Heterogeneous WSN Protocols

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