Year 2020, Volume 12 , Issue 2, Pages 587 - 602 2020-06-30

Comparison of Heuristic Algorithms via Quantum Behavior in Localization of Wireless Sensor Networks
Kablosuz Sensör Ağlarında Konum Belirlemede Sezgisel Algoritmaların Kuantum Davranışları ile Karşılaştırılması

Ertem KIZILKAPLAN [1] , Tolga EREN [2] , Fikret YALÇINKAYA [3]


Today, positioning in wireless sensor networks is becoming an important in many applications. The positioning optimization technique in WSN’s used in many applications is an important step to reach the desired goal quickly and reliably. For this reason, in the study aiming to find the targeted locations, one of the new generation heuristic algorithms created by inspiring from nature Flower Pollination Algorithm (FPA) and Cuckoo Search Algorithm (CSA) methods have been compared in solving the problem of positioning in WSN’s. In addition, Flower Pollination Algorithm (FPA) and Cuckoo Search Algorithm (CSA) are combined with quantum behavior search mechanisms to improve and compare the global search capability and accuracy of this algorithm. Quantum-behavior QFPA and QCSA applied to the test system in Matlab environment and the approaches of standard FPA and CSA to similar problem solutions were evaluated.
Günümüzde, kablosuz sensör ağlarında (KSA) konum belirleme giderek önemli bir hale gelmektedir. Bir çok uygulamada kullanılan KSA’larda konum belirleme optimizasyon tekniği, istenilen amaca doğru, hızlı ve de güvenilir bir şekilde ulaşmak için önemli bir adım oluşturmaktadır. Bu nedenle hedeflenen konumları bulmayı amaçlayan çalışmada, doğadan esinlenerek oluşturulmuş yeni nesil sezgisel algoritmalardan Çiçek Tozlaşma Algoritması (FPA) ve Guguk Kuşu Arama Algoritması (CSA) metotları (KSA)’larda konum belirleme probleminin çözülmesi amacı ile karşılaştırılmıştır. Ayrıca bu algoritmaların küresel arama kabiliyetini ve doğruluğunu geliştirmek ve karşılaştırmak amacıyla da Çiçek Tozlaşma Algoritması (FPA) ve Guguk Kuşu Arama Algoritması (CSA) kuantum davranışlı arama mekanizmalarıyla ayrı ayrı birleştirilmiştir. Matlab ortamında test sistemine uygulanmış kuantum davranışlı QFPA ve QCSA ile standart FPA ve CSA’nın benzer problem çözümüne olan yaklaşımları da değerlendirilmiştir.
  • Abdel-Basset, M. and Shawky, L.A. (2019). Flower Pollination Algorithm: A Comprehensive Review. Springer Science and Business Media B.V., part of Springer Nature. Vol. 52, pp 2533–2557, 2019.
  • Abdel-Raouf, O., Abdel-Baset, M., El-henawy, I. (2014). A New Hybrid Flower Pollination Algorithm for Solving Constrained Global Optimization Problems. International Journal of Applied Operational Research. Vol. 4, no. 2, pp. 1-13, 2014.
  • Akyildiz, I.F., Su, W. and Sankarasubramaniam, Y. (2002). Wireless Sensor Networks: A Survey. Computer Networks. Vol. 38, no. 4, pp. 393-422, 2002.
  • Alrajeh, N. A., Bashir, M. and Shams, B. (2013). Localization Techniques in Wireless Sensor Networks. Hindawi Publishing Corporation International Journal of Distributed Sensor Networks, International Journal of Distributed Sensor Networks. Vol. 13, No. 6, pp. 1-9, 2013.
  • Al-qaness, M. A. A., Ewees, A. A., Hong, F. and El Aziz, M. A. (2020). Optimization Method for Forecasting Confirmed Cases of COVID-19 in China, Journal of Clinical Medicine. Vol. 9, no. 3, 674, 2020. doi:10.3390/jcm9030674
  • Aspnes, J., Eren, T. and Goldenberg, D. (2006). A Theory of Network Localization. IEEE Transactions on Mobile Computing. Vol. 5, no. 12, pp. 1663–1678, 2006.
  • Ateş, V. and Necaattin, B. (2017). Short-Term Load Forecasting Model Using Flower Pollination Algorithm, International Scientific and Vocational Journal (ISVOS JOURNAL). Vol. 1, no.1, pp. 22-29, 2017.
  • Bekçibaşı, U., Tenruh, M. (2012). Kablosuz Algılayıcı Ağlarda Konum Saptama Teknikleri ve Mesafe Bağımlı Tekniklerde Dördüncü Çapa Yaklaşımı, Akademik Bilişim’12 - XIV. Akademik Bilişim Konferansı Bildirileri, 2012.
  • Chen, C. C., Chang, C. Y., and Li, Y. N. (2012). Range-Free Localization Scheme in Wireless Sensor Networks Based on Bilateration. Hindawi Publishing Corporation International Journal of Distributed Sensor Networks. Vol. 9, no. 1, 2012.
  • Cheng, J. and Xia, L. (2016). An Effective Cuckoo Search Algorithm for Node Localization in Wireless Sensor Network. Sensors 2016. Vol. 16, no.9, 1390, 2016. DOI:10.3390/s16091390
  • Djeloul, H., Layeb, A. and Chikhi S. (2014). Quantum Inspired Cuckoo Search Algorithm for Graph Coloring. International Journal of Bio-Inspired Computation. ISSN: 1758-0366, vol.7, no.3, pp 183–194, 2014. DOI: 10.1504/IJBIC.2015.069554
  • Doğru, A. S., Temel, B., Eren, T. (2019). dKablosuz Sensör Ağlarında Konum Belirlemede Parçacık Sürü Optimizasyonu ve Yarasa Algoritması Yöntemlerinin Karşılaştırılması. IJISAE International Journal of Intelligent Systems and Applications in Engineering, UMAGD. Vol. 11, No. 3, pp. 793-801, 2019.
  • Eren, T. (2017). The Effects of Random Geometric Graph Structure and Clustering on Localizability of Sensor Networks. International Journal of Distributed Sensor Networks, vol. 13, no.12, pp. 1-14, 2017.
  • Eren, T. (2016). Graph Invariants for Unique Localizability in Cooperative Localization of Wireless Sensor Networks: Rigidity Index and Redundancy Index, Ad Hoc Networks, vol. 44, pp. 32-45, 2016.
  • Eren, T. (2011). Cooperative Localization in Wireless ad Hoc and Sensor Networks Using Hybrid Distance and Bearing (angle of arrival) Measurements. EURASIP Journal on Wireless Communications and Networking 2011, 2011:72.
  • Eren, T. Goldenberg, D., Whiteley, W. (2004). Rigidity, Computation and Randomization in Network Localization. In Proceedings of the 2004 International Annual Joint Conference of the IEEE Computer and Communications Societies (INFOCOM 2004). Hong Kong, pp. 2673–2684.
  • Fouad, A., Zenger, K. and Gao, X. Z. (2016). A Novel Flower Pollination Algorithm Based on Genetic Algorithm Operators. Proceedings of The 9th EUROSIM Congress on Modelling and Simulation, EUROSIM 2016, The 57th SIMS Conference on Simulation and Modelling SIMS, Finland. No. 142, pp. 1060-1066, 2016. DOI: 10.3384/ecp171421060
  • Gandomi, A. H., Yang, X. S., Talatahari, S. and Alavi, A.H. (2013). Metaheuristic Algorithms in Modeling and Optimization. Metaheuristic Applications in Structures and Infrastructures. Newnes, 2013.
  • Goyal, S. and Patterh, M. S. (2015). Flower Pollination Algorithm Based Localization of Wireless Sensor Network, 2nd International Conference on Recent Advances in Engineering & Computational Sciences (RAECS), Chandigarh, pp. 1-5, 2015, DOI: 10.1109/RAECS.2015.7453299
  • Gupta, G. P., (2017). Improved Cuckoo Search-based Clustering Protokol for Wireless Sensor Networks. 6th International Conference on Smart Computing and Communications, ICSCC. Vol. 125, pp 234-240, 2017.
  • Kadıoğlu, T., Dinçer, H., Kuzlu, M. (2010). Kablosuz Duyarga Ağlarında Konum Belirleme. Elektrik, Elektronik ve Bilgisayar Mühendisliği Ulusal Konferansı (ELECO), pp. 408-413, 2010.
  • Karagül, K. (2014). Guguk Kuşu Algoritması: Bir Plastik Atık Toplama Uygulaması, 15th International Symposium on Econometrics, Operations Research and Statistic, Turkey. Vol. 15, pp. 775-784, 2014.
  • Kartous, W., Layeb, A. and Chikhi, S. (2014). New Quantum Cuckoo Search Algorithm for Multiple Sequence Alignment. Journal of Intelligent Systems, De Gruyter. Vol. 23, no.3, pp 261-275, 2014. DOI 10.1515/jisys-2013-0052
  • Keswani K. and Bhaskar A. (2018). Flower Pollination and Genetic Algortihm Based Optimization for Node Deployment in Wireless Sensor Networks. International Journal of Engineering Technologies and Management Research, Communication, Integrated Networks & Signal Processing-CINSP. Vol. 5, no. 2, pp. 281-293, 2018. DOI: 10.5281/zenodo.1244541
  • Lu, K. and Li, H. (2015). Quantum-Behaved Flower Pollination Algorithm. 14th International Symposium on Distributed Computing and Applications for Business Engineering and Science (DCABES) , pp. 66-69, 2015. DOI: 10.1109 / DCABES.2015.24
  • Lukasik, S. and Kowalski, A. (2015). Study of Flower Pollination Algorithm for Continuous Optimization In book: Intelligent Systems, 2015, DOI:10.1007/978-3-319-11313-5_40
  • Nabil, E. (2016). A Modified Flower Pollination Algorithm for Global Optimization. Expert Systems with Applications, An International Journal. Vol. 57, pp. 192-203, 2016.
  • Pan, J. S., Dao, T. K., Pan, T. S., Nguyen, T. T., Chu, S. C., Roddick, J. F. (2017). An Improvement of Flower Pollination Algorithm for Node Localization Optimization in WSN. Journal of Information Hiding and Multimedia Signal Processing, Ubiquitous International. Vol. 8, no. 2, pp. 486–499, 2017.
  • Patwari, N., Ash, J. N., Kyperountas, S. (2005). Locating The Nodes: Cooperative Localization in Wireless Sensor Networks. IEEE Signal Processing Magazine. Vol. 22, no. 4, pp. 54-69, 2005.
  • Pehlivanoğlu, Y. V. (2017). Optimizasyon: Temel Kavramlar & Yöntemler (1’nci baskı), Ankara, 2017.
  • Quaar, F. and Khelil, N. (2018). Solving Initial Value Problems by Flower Pollination Algorithm, American Journal of Electrical and Computer Engineering. Vol. 2, no. 2, pp. 31-36, 2018. DOI: 10.11648/j.ajece.20180202.14
  • Roubick, D. W. (1995). Pollination of Cultivated Plants in The Tropics. FAO Agricultural Services Bulletin 118, ISSN 1010-1365, p.196, 1995.
  • Sesli, E. and Hacıoğlu, G. (2016). RSSI and Flower Pollination Algorithm Based Location Estimation for Wireless Sensor Networks. UMAGD International Journal of Engineering Research and Development. Vol. 4, no.1, pp. 13-17, 2016.
  • Sharawi, M., Emary, E., Saroit, I. A. and El-Mahdy, H. (2014). Flower Pollination Optimization Algorithm for Wireless Sensor Network Lifetime Global Optimization, International Journal of Soft Computing and Engineering (IJSCE). ISSN: 2231-2307, vol. 4, no. 3, 2014.
  • Shrivastava, A. and Bharti, P. (2015). Localization Techniques for Wireless Sensor Networks. International Journal of Computer Applications (0975 – 8887). Vol. 116, no. 12, 2015. DOI: 10.5120 / 20387-2650
  • Singh S. P. and Sharma S. C. (2015). Range Free Localization Techniques in Wireless Sensor Networks: A Review. 3rd International Conference on Recent Trends in Computing (ICRTC). Vol. 57, pp. 7-16, 2015.
  • Sivakumar, S. and Venkatesan, R. (2014). Error Minimization in Localization of Wireless Sensor Networks using Modified Cuckoo Search with Mobile Anchor Positioning (MCS-Map) Algorithm. International Journal of Computer Applications (0975 – 8887). Vol. 95, no. 6, pp. 1-8, 2014.
  • Sun, J., Fang, W., Wu, X., Palade, V., and Xu, W. (2012). Quantum-behaved particle swarm optimization: Analysis of individual particle behavior and parameter selection. Evol. Comput. Vol. 20, no. 3, pp. 349–393, 2012. DOI: 10.1162/EVCO_a_00049
  • Türkoral, T., Tamer, Ö., Yetiş, S., İnanç, E., Çetin, L. (2016). Alınan Sinyal Gücü Göstergesi (RSSI) Metriği Kullanılarak İç Mekan Mesafe Tahmini. Elektrik, Elektronik ve Biyomedikal Mühendisliği Ulusal Konferansı (ELECO). pp. 397-401, 2016.
  • Usman, A. M, Yusof, U. K. and Naim, S. (2018). Cuckoo Inspired Algorithms for Feature Selection in Heart Disease Prediction. International Journal of Advances in Intelligent Informatics. ISSN 2442-6571, vol. 4, no. 2, pp 95–106, 2018. DOI: 10.26555/ijain.v4i2.245
  • Wang, Z., Huamao, X., He, D. and Chan, S. (2019). Wireless Sensor Network Deployment Optimization Based on Two Flower Pollination Algorithms. In IEEE Access. Vol. 7, pp. 180590-180608, 2019. DOI: 10.1109/ACCESS.2019.2959949
  • Wymeersch, H., Lien, J. and Win, M. (2009). Cooperative Localization in Wireless Networks. Proceedings of the IEEE. Vol. 97, no. 2, pp. 427-450, 2009.
  • Yang, X.S., Karamanoglu, M. and He, X. (2014). Flower Pollination Algorithm: A Novel Approach for Multiobjective Optimization. Eng Optim. Vol. 46, no. 9, pp. 1222–1237, 2014.
  • Yang, X.S. (2012). Flower Pollination Algorithm for Global Optimization. In International Conference on Unconventional Computing and Natural Computation; Springer: Berlin, Germany, pp. 240–249, 2012.
  • Yang, X.S. and Deb, S. (2009). Cuckoo Search via Levy Flights. Nature & Biologically Inspired Computing, pp. 210 - 214, 2009.
  • Yazdi, P.G. (2012). Localization of Wireless Sensor Networks for Industrial Applications. Eastern Mediterranean University, Master of Science in Mechanical Engineering, 2012.
  • Zeybekoğlu, U. (2017). Metasezgisel Optimizasyon Yöntemlerin Performanslarının Basit Bir Su Dağıtım Şebekesi Kullanılarak Araştırılması. The Black Sea Journal of Sciences (KFBD). ISSN: 2564-7377, Vol. 7, no. 2, pp. 57-67, 2017.
  • Zhang, Q., Wang, J., Jin, C., Ye, J., Changlin, M. and Zhang, W. (2008). Genetic Algorithm Based Wireless Sensor Network Localization. Proc. – 4th Int. Conf. Nat. Comput. (ICNC). Vol. 1, no. 2007, pp. 608–613, 2008. DOI: 10.1109/ICNC.2008.206
Primary Language tr
Subjects Engineering, Electrical and Electronic
Journal Section Articles
Authors

Orcid: 0000-0003-2602-4804
Author: Ertem KIZILKAPLAN (Primary Author)
Institution: KIRIKKALE ÜNİVERSİTESİ, MÜHENDİSLİK FAKÜLTESİ
Country: Turkey


Orcid: 0000-0001-5577-6752
Author: Tolga EREN
Institution: KIRIKKALE ÜNİVERSİTESİ, MÜHENDİSLİK FAKÜLTESİ
Country: Turkey


Orcid: 0000-0002-2174-918X
Author: Fikret YALÇINKAYA
Institution: KIRIKKALE ÜNİVERSİTESİ
Country: Turkey


Dates

Publication Date : June 30, 2020

APA Kızılkaplan, E , Eren, T , Yalçınkaya, F . (2020). Kablosuz Sensör Ağlarında Konum Belirlemede Sezgisel Algoritmaların Kuantum Davranışları ile Karşılaştırılması . International Journal of Engineering Research and Development , 12 (2) , 587-602 . DOI: 10.29137/umagd.746589