FEEC: fuzzy based energy efficient clustering protocol for WSN

Kumar, Ashok; Daniel, A. K.

doi:10.1007/s13198-022-01796-x

Cited by 8 publications

(2 citation statements)

References 22 publications

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“…The authors present their findings and results, highlighting the effectiveness of their proposed approach in improving the overall network performance and contributes valuable insights into optimizing CH selection in WSNs, providing potential benefits for future research and practical implementations in this field. A fuzzy logic-based clustering protocol that aims to enhance energy efficiency within WSNs was proposed in (Rai and Daniel, 2023). The paper investigates the effectiveness of FEEC in reducing energy consumption by optimizing the cluster formation process.…”

Section: Related Workmentioning

confidence: 99%

Enhancing Energy Efficiency in Cluster Based WSN using Grey Wolf Optimization

Rai,

Tyagi,

Kumar

et al. 2023

ADCAIJ

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Wireless sensor networks (WSNs) are typically made up of small, low-power sensor nodes (SNs) equipped with capability for wireless communication, processing, and sensing. These nodes collaborate with each other to form a self-organizing network. They can collect data from their surrounding environment, such as temperature, humidity, light intensity, or motion, and transmit it to a central base station (BS) or gateway for additional processing and analysis. LEACH and TSEP are examples of cluster-based protocols developed for WSNs. These protocols require careful design and optimization of CH selection algorithms, considering factors such as energy consumption, network scalability, data aggregation, load balancing, fault tolerance, and adaptability to dynamic network conditions. Various research efforts have been made to develop efficient CH selection algorithms in WSNs, considering these challenges and trade-offs. In this paper, the Grey Wolf Optimization (GWO) algorithm is employed to address the problem of selecting CHs (CHs) in WSNs. The proposed approach takes into account two parameters: Residual Energy (RE) and the distance of node (DS)s from the BS. By visualizing and analyzing the GWO algorithm under variable parameters in WSNs, this research identifies the most appropriate node from all normal nodes for CH selection. The experimental results demonstrate that the proposed model, utilizing GWO, outperforms other approaches in terms of performance.

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Section: Related Workmentioning

confidence: 99%

Enhancing Energy Efficiency in Cluster Based WSN using Grey Wolf Optimization

Rai,

Tyagi,

Kumar

et al. 2023

ADCAIJ

Self Cite

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“…Beberapa makalah yang membahas optimasi jalur pengiriman data (routing) yaitu [11]- [13]. Pembahasan teknik clustering dapat ditemukan pada [14], [15].…”

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Penghematan Daya Pada Sensor Node Sistem Monitoring Kualitas Udara

Subagiyo,

Rhamadani,

Wahyuni

2023

Indonesian J. Electron. Instrum. Syst.

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Sistem monitoring kualitas udara merupakan sistem yang digunakan untuk mengetahui indeks kualitas udara disuatu wilayah. Sensor node merupakan perangkat pengumpulan data berbasis mikroprosesor yang ditempatkan di wilayah yang dimonitor. Terkadang lokasinya berupa area terpencil dengan ketersediaan daya listrik minimal. Padahal sensor node memerlukan daya yang cukup besar terutama saat pengambilan dan pengiriman data. Oleh karena itu, diperlukan suatu sistem penghematan daya. Pada makalah ini dipaparkan sebuah rancangan sistem penghematan daya pada sensor node dengan cara memutus arus ke modul sensor pada saat tidak digunakan untuk pengambilan dan pengiriman data. Rangkaian pensaklaran MOSFET digunakan untuk memutus arus. Pengaturan jeda waktu pengambilan, pengiriman data, dan pengaktifan hemat daya, dilakukan oleh mikrokontroler. Hasil pengujian menunjukkan bahwa terjadi penghematan pemakaian energi pada sensor node sebesar 64 %. Total pemakaian energi yang digunakan selama 5 jam juga terjadi pengurangan, dari yang sebelumnya menggunakan energi sebesar 76.620 Wdtk menjadi sebesar 27.360 Wdtk.

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