Mobil Hava Baz İstasyonu İçin En İyi Konumun Bulunmasında Optimizasyon Algoritmalarının Karşılaştırılması

İnsansız hava araçları (İHA), artan uçuş süreleri, iyileştirilmiş komuta-kontrol sistemleri ve taşıma kapasiteleri sayesinde geçtiğimiz yıllarda askeri ve ticari pek çok projede başarı ile kullanılmıştır. Ancak bahsedilen araçların hizmet süre ve kalitesi genellikle daha önce belirlenen ya da anlık olarak bulunan konumlarına doğrudan bağlıdır. Bu çalışmada baz istasyon özellikli bir insansız hava aracının kullanıcılara hizmet vermesi amacı ile uygun lokasyonu Harmoni Arama (Harmony Search, HS) ve Havai Fişek (Fireworks , FW) algoritmalarından faydalanılarak bulunmaya çalışılmıştır. Elde edilen sonuçlar Parçacık Sürü Optimizasyon (Particle Swarm Optimization, PSO) ve Yapay Arı Koloni (Artificial Bee Colony, ABC) algoritmaları tarafından bulunan sonuçlar ile de karşılaştırılmıştır. Karşılaştırma sonuçları HS algoritması ile belirlenen konumlarda mobil baz istasyonunun PSO, ABC ve FW algoritmaları ile belirlenen konumlara kıyasla daha başarılı hizmet verebileceğini göstermiştir.

Comparison of Optimization Algorithms on Finding Optimum Location for Mobile Aerial Base Station

In recent years, unmanned aerial vehicles (UAVs) with the increased flying times, improved command-control systems and carrying capacities have been used successfully for the various military and commerical projects. However, the time and qualities of the services provided by the mentioned vehicles are directly related with the locations determined previously or found instantly. In this study, an appropriate location of an UAV equipped with the base station capability for serving to the users is tried to be determined by utilizing from the Harmony Search (HS) and Fireworks (FW) algorithms. The obtained results are also compared with the results obtained by the PSO and ABC algorithms. Comparative results show that the mobile base station is capable of serving more successfully when its location is determined with the HS algorithm compared to the locations determined by the ABC, PSO and FW algorithms.

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  • Al-Hourani, A. Kandeepan, S. ve Jamalipour, A., Modeling air-toground path loss for low altitude platforms in urban environments, in IEEE Global Communications Conference, pp. 2898–2904, 2014.
  • Bupe P., Haddad R., ve Rios-Gutierre, F., Relief and emergency communication network based on an autonomous decentralized uav clustering network, in IEEE SoutheastCon, pp. 1–8, 2015.
  • Shakhatreh, H. Khreishah, A. Chakareski, J. Salameh, H. B. ve Khalil, I., On the continuous coverage problem for a swarm of UAVs, in IEEE 37th Sarnoff Symposium, pp. 130–135, 2016.
  • Motlagh, N. H. Taleb, T. ve Arouk, O. Low-altitude unmanned aerial vehicles-based internet of things services: comprehensive survey and future perspectives, IEEE Internet of Things Journal, vol. 3, no. 6, pp. 899–922, 2016.
  • Gupta, L. Jain, R. ve Vaszkun, G. Survey of important issues in UAV communication networks, IEEE Comunication Surveys Tutorials, vol. 18, no. 2, pp. 1123–1152, 2016.
  • Mozaffari, M. Saad, W. Bennis, M. ve Debbah, M., Drone small cells in the clouds: desing, deployment and performance analysis, in IEEE Global Communications Conference, pp. 1–6, 2015.
  • Mozaffari, M. Saad, W. Bennis, M. ve Debbah, M., Unmanned aerial vehicle with underlaid device-to-device communications: performance and tradeoffs, IEEE Transactions on Wireless Communications, vol. 15, no. 6, pp. 3949–3963, 2016.
  • Shakhatreh, H., Khreishah, A. ve Ji, B., Providing wireless converage to high-rise buildings using uavs, in IEEE International Conference on Communications, pp. 1–6, 2017.
  • Bor-Yaliniz, R. I. El-keyfi, A. ve Yanikomeroglu, H., Efficient 3D placement of an aerial base station in next generation cellular networks, in IEEE International Conference on Communications, pp. 1–5, 2016.
  • Alzenad, M. El-keyfi, A. Lagum, F. ve Yanikomeroglu, H. 3-D placement of an unmanned aerial vehicle base station (UAV-BS) for energy-efficient maximal coverage, IEEE Wireless Communications Letters, vol. 6, no. 4, pp. 434–437, 2016.
  • Mozaffari, M. Saad, W. Bennis, M. ve Debbah, M., Efficient deployment of multiple- unmanned aerial vehicles for optimizal wireless coverage, IEEE Communication Letters, vol. 20, no. 8, pp. 1647–1650, 2016.
  • Kalantari, E. Yanikomeroglu, H. ve Yongacoglu, A., On the number and 3d placement of drone base stations in wireless cellular networks, in IEEE Vehicular Technology Conference, pp. 18–21, 2016.
  • Shakhatreh, H. Khreishah, A. Alsarhan, A. Khalil, I. Sawalmeh, A. ve N. Othman, S., Efficient 3d placement of a uav using particle swarm optimization, in IEEE 8th International Conference on Information and Communication Systems, pp. 258–263, 2017.
  • Aslan, S. ve Demirci, S. Solving UAV Localization Problem with Artificial Bee Colony (ABC) Algorithm, 2019 4th International Conference on Computer Science and Engineering (UBMK), Samsun, Turkey, 2019, pp. 735-738. doi: 10.1109/UBMK.2019.8907034
  • Geem, Z. W. Kim, J. H. ve Loganathan G. V., A new heuristic optimization algorithm: Harmony Search., Simulation, 76(2), 60-68, 2001
  • Tan, Y., Zhu, Y. Fireworks algorithm for optimization. International conference in swarm intelligence (pp. 355-364). Springer, Berlin, Heidelberg, June 2010.
  • Series, M. Guidelines for evaluation of radio interface technologies for imt-advanced, Report ITU, no. 2135-1, 2009.
  • İleri, S. C. Aslan S. ve Demirci, S., Finding Optimum Location for a Mobile Aerial Base Station with Harmony Search Algorithm, 2020 5th International Conference on Computer Science and Engineering (UBMK), Diyarbakir, Turkey, 2020, pp. 224-227, doi: 10.1109/UBMK50275.2020.9219538