KABLOSUZ HETEROJEN ALGILAYICI AĞLAR IÇIN BULANIK MANTIK TABANLI BIR KÜME BAŞI SEÇME ALGORITMASI

Year 2015, Volume: 7 Issue: 2, 48 - 59, 01.06.2015

Ali Çalhan

Abstract

Kümeleme, algılayıcı ağın yaşam süresini arttırmak için enerji tüketimini azaltan önemli bir tekniktir. Homojen kümeleme teknikleri tüm algılayıcı düğümlerin enerji miktarlarının ve özelliklerinin aynı olduğunu varsaymaktadır. Bu yüzden, geliştirilmiş küme başı seçme algoritmaları algılayıcı düğüm heterojenliğini dikkate almamaktadır. Bu çalışmada, heterojen algılayıcı ağlar için yeni bir bulanık mantık tabanlı küme başı seçme algoritması amaçlanmıştır. Veri oranı, enerji seviyesi ve mesafe parametreleri geliştirilen bulanık mantık biriminin girişleri olarak belirlenmiştir. Amaçlanan algoritma, küme başı değişim sayısı ve enerji tüketim oranı ölçütleri ile literatürdeki benzer bir bulanık mantık tabanlı algoritma ile karşılaştırılmıştır. Geliştirilen algoritma, sadece küme başı değişim sayısını azaltmakla kalmayıp enerji tüketim oranını da düğümlere göre %5 ile %75 arasında azaltmaktadır.

Keywords

heterojen kablosuz algılayıcı ağlar, kümeleme algoritması, bulanık mantık

A FUZZY LOGIC BASED CLUSTER HEAD SELECTION ALGORITHM FOR WIRELESS HETEROGENEOUS SENSOR NETWORKS

Abstract

Clustering is an important technique utilized to prolong the lifetime of a sensor network by reducing energy consumption. Homogeneous clustering techniques assume that all the sensor nodes are equipped with the same amount of energy and have the same capabilities. So, the developed cluster head selection algorithms cannot take sensor node heterogeneity into account. In this paper we propose a new fuzzy logic (FL) based cluster head selection algorithm for heterogeneous wireless sensor networks (HWSNs). The parameters, i.e., data rate, energy level and distance are considered as inputs of the developed FL unit. The proposed algorithm is compared with a FL based counterpart in the literature in terms of number of cluster head variations and energy consumption rate. The results show that the proposed FL based cluster head selection algorithm not only decreases cluster head variation dramatically but also reduces energy comsumption of heterogeneous sensor nodes between 5% and 75%.

Keywords

heterogeneous wireless sensor networks, clustering algorithm, fuzzy logic

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