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Journal from gdlhub / 2021-09-06 17:04:15
Oleh : Mohammed Ali Tawfeeq, Mahmood Zaki Abdullah, Telkomnika
Dibuat : 2021-09-06, dengan 0 file

Keyword : cluster head, network lifetime, residual energy, throughput, wireless sensor network
Url : http://journal.uad.ac.id/index.php/TELKOMNIKA/article/view/18355
Sumber pengambilan dokumen : Web

The rapid expansion in the use of IoT imposes the importance of developing its infrastructure. One of the most important components in IoT infrastructures is the wireless sensor networks. The development of these networks largely depends on how to extend their life. As one of the effective options adopted in this field is the use of cluster heads (CHs). This paper introduces an algorithm that efficiently determine the CHs by iteratively extracting an associative value for each node depending on two factors; node's residual energy, and geometrical distances between nodes and base station. In light of the extracted values, the nodes with the best associative values are elected as CHs based on adjustable threshold determined according to the network usage requirements. The algorithm has proven a significant increase in the lifetime of the network, as well as, it has proven its ability to maintain a high level of energy for long period of time. The proposed algorithm outperformed similar protocols like low energy adaptive clustering hierarchy (LEACH) and region based low energy adaptive clustering hierarchy (R-LEACH) by prolonging the network lifetime and increasing network stability, as well as enhances the throughput significantly.

Deskripsi Alternatif :

The rapid expansion in the use of IoT imposes the importance of developing its infrastructure. One of the most important components in IoT infrastructures is the wireless sensor networks. The development of these networks largely depends on how to extend their life. As one of the effective options adopted in this field is the use of cluster heads (CHs). This paper introduces an algorithm that efficiently determine the CHs by iteratively extracting an associative value for each node depending on two factors; node's residual energy, and geometrical distances between nodes and base station. In light of the extracted values, the nodes with the best associative values are elected as CHs based on adjustable threshold determined according to the network usage requirements. The algorithm has proven a significant increase in the lifetime of the network, as well as, it has proven its ability to maintain a high level of energy for long period of time. The proposed algorithm outperformed similar protocols like low energy adaptive clustering hierarchy (LEACH) and region based low energy adaptive clustering hierarchy (R-LEACH) by prolonging the network lifetime and increasing network stability, as well as enhances the throughput significantly.

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