Kablosuz Algılayıcı Ağlarda En Az Sayıda Düğüm Kullanımı için Maliyet Etkin Algılayıcı Düğüm Yerleştirme Yaklaşımı

Year 2019, , 59 - 73, 30.09.2019

Muhammed Enes Bayrakdar

https://doi.org/10.35193/bseufbd.566951

Cited By: 1

Abstract

Kablosuz algılayıcı ağlar birçok alanda yaygın
olarak kullanılan kablosuz ağ teknolojisidir. Yeraltı, karasal, sualtı ve
endüstriyel algılayıcı ağlar olmak üzere farklı kullanım alanları
bulunmaktadır. Kablosuz algılayıcı ağlardaki en önemli sorunlardan birisi, algılayıcı
düğümlerin mekanik nedenlerden dolayı arızaya meyilli olmasıdır. Diğer bir
sorun ise, kablosuz algılayıcı düğümlerin sınırlı enerjiye sahip olmasıdır. Bu
bağlamda, hata sezme mekanizmaları bulunan ve enerji verimli olarak çalışan
algılayıcı ağ tasarımları büyük önem taşımaktadır. Bunun yanında, maliyet
açısından algılayıcı düğümlerin yerleştirildiği konumları belirleme tekniği
oldukça önemlidir. Düğümlerin yerleştirildiği konumlar, hedef bölgenin bir
düğümün algılama alanı içinde olma olasılığını ve bu düğümün baz istasyonu ile
olan bağlantısını etkilemektedir. Bu makale çalışmasında, çok sayıda algılayıcı
düğümün geniş bir alana yerleştirildiği farklı bir yaklaşım önerilmektedir. Algılayıcı
düğümler; belirli bir bölgedeki sıcaklık, nem, basınç vb. parametreleri
algılamak için tüm bölgeyi kapsayacak şekilde yerleştirilmektedir. Düğümler
tarafından algılanan değerler, merkezde sabit olarak bulunan baz istasyonu
tarafından toplanmaktadır. Önerilen yaklaşımın benzetim modeli, Riverbed
Modeler yazılımı kullanılarak gerçekleştirilmiştir. Önerilen yaklaşım
sayesinde, belirli bir bölgenin en az sayıda kablosuz algılayıcı düğüm ile
sezilmesi sağlanmaktadır.

Keywords

Cihaz Maliyeti, Düğüm Yerleştirme, Enerji Tüketimi, Kablosuz algılayıcı ağ, Kapsama Alanı

Cost Efficient Sensor Node Placement Approach for Using Minimum Number of Node in Wireless Sensor Networks

Abstract

Wireless sensor networks are widely
used wireless network technology in many areas. There are different usage areas
such as underground, terrestrial, underwater and industrial sensor networks. One
of the most important problems in wireless sensor networks is that the sensor
nodes are prone to malfunction due to mechanical reasons. Another problem is
that the wireless sensor nodes have limited energy. In this context, sensor
network designs with error sensing mechanisms and energy efficient operations
are of great importance. In addition, the technique of determining the
locations where the sensor nodes are placed is very important in terms of cost.
The locations where the nodes are placed affect the probability that the target
region is within the detection area of ​​a node and its connection with the
base station. In this paper, a different approach is proposed in which a large
number of sensor nodes are placed on a large area. Sensor nodes are placed to
cover the entire region in a specific area in order to detect the parameters
such as temperature, humidity, pressure, etc. The values ​​detected by the
nodes are collected by the base station which is fixed at the center. The
simulation model of the proposed approach was performed by using Riverbed
Modeler software. Thanks to the proposed approach, it is ensured that a certain
region is sensed by the minimum number of wireless sensor nodes.

Keywords

Device Cost, Node placement, Energy Consumption, Wireless sensor network, Coverage Area

References

• [1] Tang, J., Hao, B., & Sen, A. (2006). Relay node placement in large scale wireless sensor networks. Computer Communications, 29(4), 490-501.
• [2] Liu, H., Wan, P. J., & Jia, X. H. (2006). On optimal placement of relay nodes for reliable connectivity in wireless sensor networks. Journal of Combinatorial Optimization, 11(2), 249-260.
• [3] Lloyd, E. L., & Xue, G. L. (2007). Relay node placement in wireless sensor networks. IEEE Transactions on Computers, 56(1), 134-138.
• [4] Ishizuka, M., & Aida, M. (2007). Stochastic node placement improving fault tolerance in wireless sensor networks. Electronics and Communications in Japan Part I-Communications, 90(3), 42-53.
• [5] Younis, M., & Akkaya, K. (2008). Strategies and techniques for node placement in wireless sensor networks: A survey. Ad Hoc Networks, 6(4), 621-655.
• [6] Hu, Y. M., Xue, Y. J., Li, Q., Liu, F. M., Keung, G. Y., & Li, B. (2009). The sink node placement and performance implication in mobile sensor networks. Mobile Networks & Applications, 14(2), 230-240.
• [7] Pandey, S., Dong, S. Q., Agrawal, P., & Sivalingam, K. M. (2009). On performance of node placement approaches for hierarchical heterogeneous sensor networks. Mobile Networks & Applications, 14(4), 401-414.
• [8] Misra, S., Hong, S. D., Xue, G. L., & Tang, J. (2010). Constrained relay node placement in wireless sensor networks: Formulation and approximations. IEEE-ACM Transactions on Networking, 18(2), 434-447.
• [9] Hou, Y. T., Chen, C. M., & Jeng, B. (2010). An optimal new-node placement to enhance the coverage of wireless sensor networks. Wireless Networks, 16(4), 1033-1043.
• [10] Han, X. F., Cao, X., Lloyd, E. L., & Shen, C. C. (2010). Fault-tolerant relay node placement in heterogeneous wireless sensor networks. IEEE Transactions on Mobile Computing, 9(5), 643-656.
• [11] Lu, K. Z., Chen, G. L., Feng, Y. H., Liu, G., & Mao, R. (2010). Approximation algorithm for minimizing relay node placement in wireless sensor networks. Science China-Information Sciences, 53(11), 2332-2342.
• [12] Liang, W. F., Xu, Y. L., Shi, J. G., & Luo, J. Z. (2012). Aggregate node placement for maximizing network lifetime in sensor networks. Wireless Communications & Mobile Computing, 12(3), 219-235.
• [13] Lee, S., & Younis, M. (2012). Optimized relay node placement for connecting disjoint wireless sensor networks. Computer Networks, 56(12), 2788-2804.
• [14] Chen, F. C., & Li, R. L. (2013). Sink node placement strategies for wireless sensor networks. Wireless Personal Communications, 68(2), 303-319.
• [15] Tapiador, J. E., & Clark, J. A. (2013). The placement-configuration problem for intrusion detection nodes in wireless sensor networks. Computers & Electrical Engineering, 39(7), 2306-2317.
• [16] Kimence, S., & Bekmezci, I. (2014). Weighted relay node placement for wireless sensor network connectivity. Wireless Networks, 20(4), 553-562.
• [17] Wu, D. L., Chatzigeorgiou, D., Youcef-Toumi, K., Mekid, S., & Ben-Mansour, R. (2014). Channel-aware relay node placement in wireless sensor networks for pipeline inspection. IEEE Transactions on Wireless Communications, 13(7), 3510-3523.
• [18] Ranga, V., Dave, M., & Verma, A. K. (2015). Relay node placement to heal partitioned wireless sensor networks. Computers & Electrical Engineering, 48, 371-388.
• [19] Ma, C. F., Liang, W., Zheng, M., & Sharif, H. (2016). A connectivity-aware approximation algorithm for relay node placement in wireless sensor networks. IEEE Sensors Journal, 16(2), 515-528.
• [20] Vikrant, S., Patel, R. B., Bhadauria, H. S., & Prasad, D. (2016). Policy for planned placement of sensor nodes in large scale wireless sensor network. KSII Transactions on Internet and Information Systems, 10(7), 3213-3230.
• [21] Bagaa, M., Chelli, A., Djenouri, D., Taleb, T., Balasingham, I., & Kansanen, K. (2017). Optimal placement of relay nodes over limited positions in wireless sensor networks. IEEE Transactions on Wireless Communications, 16(4), 2205-2219.
• [22] Njoya, A. N., Thron, C., Barry, J., Abdou, W., Tonye, E., Konje, N. S. L., & Dipanda, A. (2017). Efficient scalable sensor node placement algorithm for fixed target coverage applications of wireless sensor networks. IET Wireless Sensor Systems, 7(2), 44-54.
• [23] Chang, C. Y., Chin, Y. T., Chen, C. C., & Chang, C. T. (2018). Impasse-aware node placement mechanism for wireless sensor networks. IEEE Transactions on Systems Man Cybernetics-Systems, 48(8), 1225-1237.
• [24] Cheng, Z., Perillo, M., & Heinzelman, W. B. (2008). General network lifetime and cost models for evaluating sensor network deployment strategies. IEEE Transactions on Mobile Computing, 7(4), 484-497.
• [25] Akyildiz, I. F., Su, W., Sankarasubramaniam, Y., & Cayirci, E. (2002). Wireless sensor networks: a survey. Computer Networks, 38(4), 393-422.
• [26] Vuran, M. C., Akan, Ö. B., & Akyildiz I. F. (2004). Spatio-temporal correlation: theory and applications for wireless sensor networks. Computer Networks, 45(3), 245-259.
• [27] Soman, R., Kudela, P., Balasubramaniam, K., Singh, S. K., & Malinowski, P. (2019). A study of sensor placement optimization problem for guided wave-based damage detection. Sensors, 19(8), 1-18.
• [28] Demetri, S., Picco, G. P., & Bruzzone L. (2019). LaPS: LiDAR-assisted placement of wireless sensor networks in forests. ACM Transactions on Sensor Networks, 15(2), 1-40.
• [29] Nandy, A., Chakraborty, D., & Shah M. S. (2019). Optimal sensors/actuators placement in smart structure using island model parallel genetic algorithm. International Journal of Computational Methods, 16(6), Special Issue.
• [30] Trothe, M. E. S., Shaker, H. R., Jradi, M., & Arendt K. (2019). Fault isolability analysis and optimal sensor placement for fault diagnosis in smart buildings. Energies, 12(9), 1-12.
• [31] Jo, T., Koo, B., Kim, H., Lee, D., & Yoon J. Y. (2019). Effective sensor placement in a steam reformer using gappy proper orthogonal decomposition. Applied Thermal Engineering, 154, 419-432.
• [32] Blachowski, B. (2019). Modal sensitivity based sensor placement for damage identification under sparsity constraint. Periodica Polytechnica-Civil Engineering, 63(2), 432-445.
• [33] Spinelli, B., Celis, L. E., & Thiran P. (2019). A general framework for sensor placement in source localization. IEEE Transactions on Network Science and Engineering, 6(2), 86-102.
• [34] Riverbed Modeler, S. S. (2019). Benzetim Yazılımı. San Francisco, USA, https://www.riverbed.com/gb/, (30 Nisan 2019).