Kablosuz Sensör Ağları için Geliştirilmiş SEED Kümeleme Modeli

Kablosuz Sensör ağlarında (KSA) verimli bir şekilde veri toplamak için kümeleme yöntemleri geliştirmek önemlidir. Literatürdeki kümeleme yöntemleri arasında, dengeli enerji tüketimi ve ağın ömrünün uzatılması adına en popüler olanı, farklı özelliklere sahip düğümlerden oluşan heterojen kümelemedir. Bu çalışmada, heterojen bir kümeleme olan Uyku-Uyanık Enerji Verimli Dağıtılmış (Sleep-awake Energy Efficient Distributed, SEED) kümeleme yöntemi geliştirilmiştir. Bu anlamda, SEED mekanizması veri gönderme-alma ve enerji tüketimi adına geliştirilmiştir. Önerilen yönteme göre, KSA'daki düğümler verileri belirli zaman aralıklarında algılar ve belirli zamanlarda uyuyarak veri iletmez ve almaz. Önerilen algoritmanın SEED yönteminden en önemli farkı, düğümlerin kalan enerjisinin ve ağ ortalama enerjisinin, küme başı (KB) seçimindeki eşik değerine eklenmiş olmasıdır. Ayrıca, küme oluşumu ve KB seçimi, küme üyelerinin KB'lerle iletişim kurmasını sağlayarak SEED algoritmasından daha etkili bir yöntem sağlar ve daha sonra veri iletim süreci de yöntem sürecine dahil edilir. Böylece, optimum KB'ler seçilerek enerji tüketimi azaltılır ve ağ ömrü uzatılır. Önerilen yöntem hem SEED algoritması hem de simülasyon ortamında literatürde bulunan diğer heterojen kümeleme yöntemleri ile karşılaştırılmıştır. Simülasyonların sonuçları önerilen yöntemin avantajlarını göstermektedir.

An improved SEED clustering model for wireless sensor networks

It is important to develop clustering methods to collect data efficiently in wireless sensor networks (WSNs). Among the clusteringmethods in the literature, the most popular on behalf of balanced energy depletion and increasing the life of the network isheterogeneous clustering consisting of nodes with different characteristics. In this study, Sleep-awake Energy Efficient Distributed(SEED) clustering method that is a heterogeneous clustering, has been improved. In this sense, the mechanism of the SEED hasbeen developed on behalf of the data sending-receiving, and energy consumption. According to the proposed method, the nodes inthe WSN perceive the data in specified time periods and do not transmit and receive data by staying asleep at certain times. Themost important difference of the proposed algorithm from the SEED method is that the remaining energy of the nodes and thenetwork average energy are added to the threshold value in the cluster head (CH) selection. Moreover, cluster formation and CHselection enables more effective method than SEED algorithm by providing cluster members to communicate with CHs, and thenthe data transmission process is also included in the method process. Thus, energy consumption is reduced and network life iselongated by choosing the optimum CHs. The proposed method has been compared with both the SEED algorithm and otherheterogeneous clustering methods existing in the literature in the simulation environment. The results of the simulations show theadvantages of the recommended method.

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