Mesut UĞURLU, Abdullah ORMAN, Murat DENER

Komşuluk Yaklaşımı ile Kablosuz Sensör Ağlarda Izgara Temelli Kümeleme Tasarımı ve Uygulaması

Kablosuz sensör ağlar, medikal, askeri, endüstriyel, tarım ve çevresel uygulamada alanı izlemek için yoğun olarak kullanılmaktadır. Bu ağlarda birçok sensör düğüm bulunmaktadır ve bu düğümler kısıtlı kaynaklar sahiptir. Ayrıca bu sensör düğümler tekrar şarj özelliğinin çok olmaması nedeni ile enerjilerini bittiği durumlarda tekrar kullanılamaz hale gelmektedir. Enerji tüketiminin verimli kullanılması bu ağlardaki en önemli çalışma alanlarından biridir. Kümeleme yaklaşımı düğümlerin dağıtıldığı alanı kümelere ayırır ve her küme için bir küme başı seçer. Küme başı küme içerisinde bulunan sensör düğümlerden algılanan verileri toplar, birleştirir ve baz istasyonuna iletir. Kümeleme enerji tüketimini azaltarak ağın ömrünü uzatır. Bu çalışmada ızgara temelli kümeleme işlemi yapılmış ve en çok komşuluğa sahip düğüm küme başı olarak seçilmiştir. Küme başı enerjisi azaldığında ilgili küme içerisinde en çok ikincil komşuluğa sahip düğüm küme başı seçilmektedir. Önerilen yöntem MATLAB simülasyon ortamında gerçekleştirilmiştir. Çalışmada elde edilen bulgular incelendiğinde önerilen yöntemin, kümeleme yapılmadan oluşturulan ağlara kıyasla %60 daha uzun ömürlü olduğu ve sensör düğümlerde enerji tüketiminin verimli hale getirildiği gözlemlenmiştir.

Anahtar Kelimeler:

Kablosuz sensör ağlar, Izgara temelli kümeleme, Komşuluk yaklaşımı

Grid Based Clustering Design and Implementation in Wireless Sensor Networks with Neighborhood Approach

Wireless sensor networks are extensively used to monitor field in medical, military, industrial, agricultural and environmental application. There are many sensor nodes in these networks and these nodes have limited resources. In addition, these sensor nodes become unusable when they run out of energy due to the lack of recharging feature. Efficient use of energy consumption is one of the most important working areas in these networks. The clustering approach divides the area where the nodes are distributed into clusters and selects a cluster head for each cluster. The cluster head collects the data detected from the sensor nodes in the cluster, combines it and transmits it to the base station. Clustering reduces energy consumption and extends the life of the network.In this study, grid-based clustering was performed and the node with the most neighbors was chosen as the cluster head. When the cluster head energy decreases, the node with the most secondary neighbors in the related cluster is selected as the cluster head. The proposed method was implemented in the MATLAB simulation environment. When the findings obtained in the study are examined, it has been observed that the proposed method has a much longer life than the networks created without clustering and the energy consumption in the sensor nodes is made efficient.

Keywords:

Wireless sensor networks, Grid-based clustering, Neighborhood approach,

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[1] V. Potdar, A. Sharif and E. Chang, “Wireless Sensor Networks: A Survey,” in International Conference on Advanced Information Networking and Applications Workshops, Bradford, United Kingdom, 2009, pp. 636-641. [2] M. Pule, A. Yahya and J. Chuma, “Wireless sensor networks: A survey on monitoring water quality,” Journal of Applied Research and Technology, vol. 15, no. 6, pp. 562-570, 2017. [3] M. Dener, “Kablosuz Sensör Ağlar ile Yeri Tespit Edilen Doktorların Konum Bilgilerinin Android ve Web Tabanlı Platformlar Üzerinden Görüntülenmesi,” Bilişim Teknolojileri Dergisi, c. 11, s. 2, ss. 203-210, 2018. [4] J. Yick, B. Mukherjee and D. Ghosal, “Wireless sensor network survey,” Computer Networks, vol. 52, pp. 2292-2330, 2008. [5] M. F. Othman and K. Shazali, “Wireless Sensor Network Applications: A Study in Environment Monitoring System,” Procedia Engineering, vol. 41, pp. 1204-1210, 2012. [6] N. Srivastava, “Challenges of Next-Generation Wireless Sensor Networks and its impact on Society,” Journal of Telecommunıcatıons, vol. 1, no. 1, pp. 128-133, 2010. [7] T. Bala, V. Bhatia, S. Kumawat and V. Jaglan, “A survey: issues and challenges in wireless sensor network,” International Journal of Engineering & Technology, vol. 7, no. 2.4, pp. 53-55, 2018. [8] I. F. Akyildiz, W. Su, Y. Sankarasubramaniam and E. Cayirci, "A survey on sensor networks," IEEE Communications Magazine, vol. 40, no. 8, pp. 102-114, 2002. [9] S. Dhiviya, A. Sariga and P. Sujatha, "Survey on WSN Using Clustering," in 2017 Second International Conference on Recent Trends and Challenges in Computational Models (ICRTCCM), Tindivanam, Tamilnadu, India, 2017, pp. 121-125. [10] M. M. Raouf, “Clustering in Wireless Sensor Networks (WSNs),” Journal Of Baghdad Unıversıty College of Economıc Scıences, vol. 57, 2019. [11] M. C. M. Thein and T. Thein, “A Framework for Secure and Survivable Wireless Sensor Networks,” Annals of Dunărea de Jos University. Fascicle I : Economics and Applied Informatics., pp. 243-252, 2009. [12] P. Kumar, M. P. Singh and U. S. Triar, “A Review of Routing Protocols in Wireless Sensor Network,” International Journal of Engineering Research & Technology, vol. 1, no. 4, pp. 1-14, 2012. [13] I. Ouafaa, K. S. Ddine, L. Jalal and E. H. Said, “Recent Advances of Hierarchical Routing Protocols for AdHoc and Wireless Sensor Networks: A Literature Survey,” Bilişim Teknolojileri Dergisi, vol. 9, no. 2, pp. 71-79, 2016. [14] W. R. Heinzelman, A. Chandrakasan and H. Balakrishnan, "Energy-efficient communication protocol for wireless microsensor networks," in Proceedings of the 33rd Annual Hawaii International Conference on System Sciences, Maui, Hawaii, 2000, pp. 1-10. [15] L. Li, X. Jiang, S. Zhong and L. Hu, "Energy Balancing Clustering Algorithm for Wireless Sensor Network," in International Conference on Networks Security, Wireless Communications and Trusted Computing, Wuhan, China, 2009, pp. 61-64. [16] W. Liu, Z. Wang, S. Zhang and Q. Wang, "A Low Power Grid-Based Cluster Routing Algorithm of Wireless Sensor Networks," in International Forum on Information Technology and Applications, Kunming, Yunnan, China, 2010, pp. 227-229. [17] P. K. J. Srikanth Jannu, “Energy Efficient Grid Based Clustering and Routing Algorithms for Wireless Sensor Networks,” in Fourth International Conference on Communication Systems and Network Technologies, Newyork Washington, DC, United States, 2014, pp. 63-68. [18] M. Abdullah, H. N. Eldin, T. Al-Moshadak, R. Alshaik and I. Al-Anesi, “Density Grid-Based Clustering for Wireless Sensors Networks,” Procedia Computer Science, vol. 65, pp. 35-47, 2015. [19] S. Jannu and P. K. Jana, “A grid based clustering and routing algorithm for solving hot spot problem in wireless sensor networks,” Wireless Networks, vol. 22, no. 6, pp. 1901-1916, 2016. [20] M. M. Kareem, M. Ismail, M. A. Altahrawi, N. Arsad, M. F. Mansor and A. H. Ali, "Grid Based Clustering Technique in Wireless Sensor Network using Hierarchical Routing Protocol," in IEEE 4th International Symposium on Telecommunication Technologies (ISTT), Selangor, Malaysia, 2018, pp. 1-5. [21] A. A. Kamil, M. K. Naji and H. A. Turki, “Design and implementation of grid based clustering in WSN using dynamic sink node,” Bulletin of Electrical Engineering and Informatics, vol. 9, no. 5, pp. 2055-2064, 2020. [22] B. S. Hassen, A. Lafta, H. Noman and A. H. Ali, “Analyzing the Performances of WSNs Routing Protocols in Grid-Based Clustering,” International Journal on Advanced Science Engineering and Information Technology, vol. 9, no. 4, pp. 1211-1216, 2019. [23] K. R. Bhakare, R. K. Krishna and S. Bhakare, “An Energy-efficient Grid based Clustering Topology for a Wireless Sensor Network,” International Journal of Computer Applications, vol. 39, no. 14, pp. 24-28, 2012. [24] H. Zhou, D. Luo, Y. Gao and D. Zuo, “Modeling of Node Energy Consumption for Wireless Sensor Networks,” Wireless Sensor Network, vol. 3, no. 1, pp. 18-23, 2011.