Energy efficient data aggregation in wireless sensor networks

Padmaja, P.; Marutheswar, G. V.

doi:10.1016/j.matpr.2017.11.096

Cited by 10 publications

(9 citation statements)

References 7 publications

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“…The key benefit of using this technique was minimizing controlling overhead, and increased energy efficiency. Gopalakrishnan et al 31 discussed many areas, such as mobile devices and the military in a disaster situation and other crisis situations, the currently emerging communication infrastructure is in great demand. Gopalakrishnan et al 32 discussed improvement of efficient packet access in a wireless network is vital for achieving high speed data rate.…”

Section: Related Workmentioning

confidence: 99%

A classy energy efficient spider monkey optimization based clustering and data aggregation models for wireless sensor network

Arunachalam

Vimal

Gomathi³

et al. 2022

Concurrency and Computation

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SUMMARY Establishment of energy efficient and reliable data routing in wireless sensor network (WSN) is one of the most critical and challenging task in the recent days. Also, the overall performance and lifetime of WSN is highly depends on the energy level of sensor nodes, hence it is most essential to save the energy of network. For this purpose, the different types of clustering and data aggregation mechanisms are developed in the conventional works, which are focusing on improving both the energy conservation and lifetime of network. Yet, it facing the challenges of increased computational complexity, inefficient routing of data, high controlling overhead, and reduced reliability. Thus, the proposed work objects to develop a novel energy efficient mechanism by integrating the functionalities of advanced clustering, path selection, and data aggregation methodologies. Here, the spider monkey optimization based energy efficient routing protocol is developed for optimally selecting the cluster head (CH) based on certain parameters of energy, distance, and weight value. In this framework, the data transmission is performed between the source to destination nodes through the relay nodes and CHs, which helps to minimize the energy consumption of network. Then, the Classy Bellman‐Ford algorithm is deployed for identifying the best paths having shortest distance with the sink nodes. Consequently, an anticipated data aggregation mechanism is utilized for ensuring the security and reliability of data transmission in WSN. For evaluation assessment, various performance metrics have been utilized to validate the results of proposed methodology, and also the obtained values are compared with some other recent state‐of‐the‐art models for proving the betterment of proposed mechanism.

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Section: Related Workmentioning

confidence: 99%

A classy energy efficient spider monkey optimization based clustering and data aggregation models for wireless sensor network

Arunachalam

Vimal

Gomathi³

et al. 2022

Concurrency and Computation

View full text Add to dashboard Cite

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“…However, data aggregation techniques may reduce the accuracy of the collected data. Indeed, depending on the aggregation function, original data may not be recovered by the sink, thus information precision can be lost [20].…”

Section: Aggregationmentioning

confidence: 99%

A Survey of Energy Efficiency in Wireless Human Body Sensors Lifetime for Healthcare Applications

Kassan¹

2019

TTEH

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“…Pengurangan jumlah data yang dikirimkan pada jaringan sensor nirkabel telah diteliti sebelumnya dengan metode agregasi data [6]. Pada metode ini, semua data dikumpulkan dalam suatu node kemudian diproses dan digabungkan yang menghasilkan satu data baru yang mewakili semua data yang telah dikumpulkan.…”

Section: Algoritma Dynamic Cluster Head Dengan Metode Rating Untuk Meunclassified

Algoritma Dynamic Cluster Head dengan Metode Rating untuk Mengurangi Dead Node pada Jaringan Sensor Nirkabel

Kusuma¹

2019

eksplora

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Jaringan sensor nirkabel terdiri dari node-node sensor yang memiliki sumber daya energi yang terbatas. Jaringan ini dibangun untuk mengawasi lingkungan dan memberikan informasi ke sebuah koordinator. Namun karena node yang berjalan dengan sumber daya terbatas seperti baterai, diperlukan sebuah protokol yang mampu memanfaatkan sumber daya yang terbatas namun data yang disampaikan tetap terjaga. In-network data aggregation merupakan sebuah metode agregasi pengumpulan data routing melalui jaringan multi-hop, mengolah data pada intermediate node dengan tujuan meningkatkan network lifetime. Agregasi data dilakukan secara terpusat pada topologi Tree-Based Network yang diproses pada Cluster Head sehingga memberikan beban pada Cluster Head yang mengakibatkan konsumsi energi terpusat pada satu node. Penelitian ini menghasilkan algoritma penentuan node yang bertugas menjadi Cluster Head sesuai dengan kondisi jaringan secara dinamis yang disebut A-SEClush. Berdasarkan hasil uji coba yang telah dilakukan algoritma ini memiliki keunggulan sebesar 2,0 pada total node yang mengalami kehabisan energi dibandingkan dengan Static-CH.

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Energy efficient data aggregation in wireless sensor networks

Cited by 10 publications

References 7 publications

A classy energy efficient spider monkey optimization based clustering and data aggregation models for wireless sensor network

A classy energy efficient spider monkey optimization based clustering and data aggregation models for wireless sensor network

A Survey of Energy Efficiency in Wireless Human Body Sensors Lifetime for Healthcare Applications

Algoritma Dynamic Cluster Head dengan Metode Rating untuk Mengurangi Dead Node pada Jaringan Sensor Nirkabel

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