Kablosuz Sensör Ağlarında Konum Belirlemede Parçacık Sürü Optimizasyonu ve Yarasa Algoritması Yöntemlerinin Karşılaştırılması

Year 2019, Volume: 11 Issue: 3, 793 - 801, 31.12.2019

Ahmet Sami Doğru , Burak Temel Tolga Eren

https://doi.org/10.29137/umagd.668724

Cited By: 4

Abstract

Kablosuz sensör ağlarında konum belirleme birçok uygulamada her geçen gün önemli bir konu haline gelmektedir. Arama kurtarma, doğal afet, coğrafi izleme ve takip gibi uygulamalarda sensörlerin konumunu doğru ve hızlı bir şekilde tespit etmek çok önemlidir. Kablosuz sensör ağlarında (KSA), konum belirleme çok boyutlu bir optimizasyon problemi olarak ifade edilmektedir. KSA’ların karmaşıklığına göre optimizasyon yöntemlerinin performansları da değişmektedir. Bu çalışmada, Parçacık Sürü Optimizasyonu (PSO) ve Yarasa Algoritması (YA) metotları KSA’larda konum belirleme probleminin çözülmesi amacı ile karşılaştırılmıştır. Önerilen yöntemler, doğada yaşayan varlıkların hareketinden esinlenerek geliştirilmiş optimizasyon yöntemleridir. Bu çalışmada sezgisel optimizasyon metotlarından olan PSO ve YA, Matlab ortamında test sistemine uygulanmış olup sonuçlar değerlendirilmiştir.

Keywords

Parçacık sürü optimizasyonu, Yarasa algoritması, Kablosuz sensör ağlarında konum belirleme

Comparison of Particle Swarm Optimization and Bat Algorithm Methods in Localization of Wireless Sensor Networks

Abstract

Positioning in wireless sensor networks is becoming an important issue in many applications. It is very important to accurately and quickly determine the position of sensors in applications such as search and rescue, natural disaster, geographical monitoring and tracking. In wireless sensor networks (WSN), positioning is expressed as a multidimensional optimization problem. According to the complexity of WSN’s, the performance of optimization methods also changes. In this article, Particle Swarm Optimization (PSO) and Bat Algorithm (BA) methods have been compared in solving the problem of positioning in WSN’s. The proposed methods are optimization methods inspired by the movement of living beings in nature. In this study, one of the heuristic optimization methods, PSO and BA, was applied to the test system in Matlab environment and the results were evaluated.

Keywords

Particle swarm optimization, Bat algorithm, Localization in wireless sensor networks

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