oalogo2  

AUTHOR(S):

Ira Tuba, Viktor Tuba

 

TITLE

Node Localization in Wireless Sensor Networks by Water Cycle Algorithm

pdf PDF

ABSTRACT

Wireless sensor networks have numerous practical uses which make them interesting and active research topic. Beside the information collected by wireless sensor networks, usually location of the sensor is necessary in order to have complete and useful information. Since it is rather expensive to put GPS receivers in all sensors, different localization techniques were developed. Usually a small number of nodes are equipped by GPS receiver while the location of the rest nodes is determined based on the received signal strength. Finding the positions of sensors is a hard optimization problem and in this paper we propose recent swarm intelligence optimization algorithm - water cycle algorithm. The proposed method was compared to other methods from literature and it was proved to be better considering all quality indicators.

KEYWORDS

water cycle algorithm, global optimization, swarm intelligence, metaheuristics, wireless sensor networks, localization

REFERENCES

[1] B. R. Stojkoska, A. P. Avramova, and P. Chatzimisios, “Application of wireless sensor networks for indoor temperature regulation,” International Journal of Distributed Sensor Networks, vol. 2014, 2014.

[2] P. Rawat, K. D. Singh, H. Chaouchi, and J. M. Bonnin, “Wireless sensor networks: a survey on recent developments and potential synergies,” The Journal of Supercomputing, vol. 68, pp. 1– 48, April 2014.

[3] W. Dargie and C. Poellabauer, Fundamentals of Wireless Sensor Networks: Theory and Practice. No. 978-0-470-99765-9, Wiley, 2010.

[4] M. A. Ameen, J. Liu, and K. Kwak, “Security and privacy issues in wireless sensor networks for healthcare application,” Journal of Medical Systems, vol. 36, no. 1, pp. 93–101, 2012.

[5] M. Winkler, K. Tuchs, K. Hughes, and G.Barclay, “Theoretical and practical aspects of military wireless sensor networks,” Journal of Telecommunication and Information Technology, vol. 2, pp. 37–45, 2008.

[6] X.-S. Yang, “Firefly algorithm, stochastic test functions and design optimisation,” International Journal of Bio-Inspired Computation, vol. 2, no. 2, pp. 78–84, 2010.

[7] E. Tuba, M. Tuba, and D. Simian, “Adjusted bat algorithm for tuning of support vector machine parameters,” in IEEE Congress on Evolutionary Computation (CEC), pp. 2225–2232, IEEE, 2016.

[8] E. Tuba, M. Tuba, and D. Simian, “Handwritten digit recognition by support vector machine optimized by bat algorithm,” Proceeding of the WSCG 2016, Computer Science Research Notes, pp. 369–376, 2016.

[9] M. Tuba and N. Bacanin, “Hybridized bat algorithm for multi-objective radio frequency identification (RFID) network planning,” in Proceedings of the 2015 IEEE Congress on Evolutionary Computation (CEC 2015), May 2015.

[10] Y. Tan and Y. Zhu, “Fireworks algorithm for optimization,” Advances in Swarm Intelligence, LNCS, vol. 6145, pp. 355–364, June 2010.

[11] E. Tuba, M. Tuba, and E. Dolicanin, “Adjusted fireworks algorithm applied to retinal image registration,” Studies in Informatics and Control, vol. 26, pp. 33–42, March 2017.

[12] E. Tuba, M. Tuba, D. Simian, and R. Jovanovic, “JPEG quantization table optimization by guided fireworks algorithm,” Combinatorial Image Analysis IWCIA 2017, Lecture Notes in Computer Science, vol. 10256, pp. 294–307, 2017.

[13] M. Tuba, N. Bacanin, and A. Alihodzic, “Multilevel image thresholding by fireworks algorithm,” in 2015 25th International Conference Radioelektronika (RADIOELEKTRONIKA), pp. 326–330, April 2015.

[14] E. Tuba, M. Tuba, and M. Beko, “Support vector machine parameters optimization by enhanced fireworks algorithm,” Advances in Swarm Intelligence ICSI 2016, Lecture Notes in Computer Science, vol. 9712, pp. 526–534, 2016.

[15] E. Tuba, E. Dolicanin, and M. Tuba, “Chaotic brain storm optimization algorithm,” in Intelligent Data Engineering and Automated Learning, LNCS, vol. 10585, (Cham), pp. 551–559, Springer International Publishing, 2017.

[16] E. Dolicanin, I. Fetahovic, E. Tuba, R. Capor- Hrosik, and M. Tuba, “Unmanned combat aerial vehicle path planning by brain storm optimization algorithm,” Studies in Informatics and Control, vol. 27, no. 1, pp. 15–24, 2018.

[17] E. Tuba, R. Capor-Hrosik, A. Alihodzic, and M. Tuba, “Drone placement for optimal coverage by brain storm optimization algorithm,” in International Conference on Health Information Science, Advances in Intelligent Systems and Computing, vol. 734, pp. 167–176, Springer, 2017.

[18] G.-G.Wang, S. Deb, and L. dos S. Coelho, “Elephant herding optimization,” in Proceedings of the 2015 3rd International Symposium on Computational and Business Intelligence (ISCBI), pp. 1–5, December 2015.

[19] I. Strumberger, N. Bacanin, M. Beko, S. Tomic, and M. Tuba, “Static drone placement by elephant herding optimization algorithm,” in Proceedings of the 24th Telecommunications Forum (TELFOR), November 2017.

[20] A. Alihodzic, E. Tuba, R. Capor-Hrosik, E. Dolicanin, and M. Tuba, “Unmanned aerial vehicle path planning problem by adjusted elephant herding optimization,” in 25th Telecommunication Forum (TELFOR), pp. 1–4, IEEE, 2017.

[21] E. Tuba, I. Ribic, R. Capor-Hrosik, and M. Tuba, “Support vector machine optimized by elephant herding algorithm for erythemato-squamous diseases detection,” Procedia Computer Science, vol. 122, pp. 916–923, 2017.

[22] E. Tuba and Z. Stanimirovic, “Elephant herding optimization algorithm for support vector machine parameters tuning,” in Proceedings of the 2017 International Conference on Electronics, Computers and Artificial Intelligence (ECAI), pp. 1–5, June 2017.

[23] E. Tuba, A. Alihodzic, and M. Tuba, “Multilevel image thresholding using elephant herding optimization algorithm,” in Proceedings of 14th International Conference on the Engineering of Modern Electric Systems (EMES), pp. 240–243, June 2017.

[24] E. Tuba, M. Tuba, and M. Beko, “Node localization in ad hoc wireless sensor networks using fireworks algorithm,” in Proceedings of the 5th International Conference on Multimedia Computing and Systems (ICMCS), pp. 223–229, September 2016.

[25] N. Patwari, J. N. Ash, S. Kyperountas, A. O. Hero, R. L. Moses, and N. S. Correal, “Locating the nodes: cooperative localization in wireless sensor networks,” IEEE Signal Processing Magazine, vol. 22, pp. 54–69, July 2005.

[26] E. Tuba, M. Tuba, and M. Beko, “Two stage wireless sensor node localization using firefly algorithm,” in Smart Trends in Systems, Security and Sustainability, LNNS, vol. 18, pp. 113–120, Springer, 2018.

[27] M. Vecchio, R. Lpez-Valcarce, and F. Marcelloni, “A two-objective evolutionary approach based on topological constraints for node localization in wireless sensor networks,” Applied Soft Computing, vol. 12, no. 7, pp. 1891 – 1901, 2012. Soft Computing Approaches in the design of energy-efficient wireless systems.

[28] E. Tuba, M. Tuba, and D. Simian, “Wireless sensor network coverage problem using modified fireworks algorithm,” in International Wireless Communications and Mobile Computing Conference (IWCMC), pp. 696–701, IEEE, 2016.

[29] E. Tuba, M. Tuba, and M. Beko, “Mobile wireless sensor networks coverage maximization by firefly algorithm,” in 27th International Conference Radioelektronika, pp. 1–5, IEEE, 2017.

[30] H. Eskandar, A. Sadollah, A. Bahreininejad, and M. Hamdi, “Water cycle algorithm– a novel metaheuristic optimization method for solving constrained engineering optimization problems,” Computers & Structures, vol. 110, pp. 151–166, 2012.

[31] S. Sivakuma and R. Venkatesan, “Error minimization in localization of wireless sensor networks using differential evolution with mobile anchor positioning (DE - MAP) algorithm,” Journal of Theoretical and Applied Information Technology, vol. 66, pp. 330 – 339, August 2014.

[32] N. Bulusu, J. Heidemann, V. Bychkovskiy, and D. Estrin, “Density-adaptive beacon placement algorithms for localization in ad hoc wireless networks,” in In Proceedings of the 21st Annual Joint Conference of the IEEE Computer and Communications Societies (INFOCOM-21), New York, June 2002.

[33] N. Bulusu, J. Heidemann, V. Bychkovskiy, and D. Estrin, “Adaptive beacon placement,” in In Proceedings of the 21st International Conference on Distributed Computing Systems (ICDCS-21), pp. 489 – 498, April 2001.

[34] A. Sadollah, H. Eskandar, A. Bahreininejad, and J. H. Kim, “Water cycle algorithm with evaporation rate for solving constrained and unconstrained optimization problems,” Applied Soft Computing, vol. 30, pp. 58–71, 2015.

[35] A. Sadollah, H. Eskandar, A. Bahreininejad, and J. H. Kim, “Water cycle algorithm for solving multi-objective optimization problems,” Soft Computing, vol. 19, no. 9, pp. 2587–2603, 2015.

[36] A. Sadollah, H. Eskandar, and J. H. Kim, “Water cycle algorithm for solving constrained multiobjective optimization problems,” Applied Soft Computing, vol. 27, pp. 279–298, 2015.

[37] A. A. Heidari, R. A. Abbaspour, and A. R. Jordehi, “An efficient chaotic water cycle algorithm for optimization tasks,” Neural Computing and Applications, vol. 28, no. 1, pp. 57–85, 2017.

[38] O. B. Haddad, M. Moravej, and H. A. Lo´aiciga, “Application of the water cycle algorithm to the optimal operation of reservoir systems,” Journal of Irrigation and Drainage Engineering, vol. 141, no. 5, p. 04014064, 2014.

[39] H. Eskandar, A. Sadollah, and A. Bahreininejad, “Weight optimization of truss structures using water cycle algorithm,” vol. 3, no. 1, 2013.

[40] A. Deihimi, B. K. Zahed, and R. Iravani, “An interactive operation management of a microgrid with multiple distributed generations using multi-objective uniform water cycle algorithm,” Energy, vol. 106, pp. 482–509, 2016.

[41] A. A. Heidari, R. A. Abbaspour, and A. R. Jordehi, “Gaussian bare-bones water cycle algorithm for optimal reactive power dispatch in electrical power systems,” Applied Soft Computing, vol. 57, pp. 657–671, 2017.

[42] N. Wet, Q. Guo, M.-L. Shu, J.-l. Lu, and M. Yang, “Three-dimensional localization algorithm of wireless sensor networks based on particle swarm optimization,” The Journal of China Universities of Posts and Telecommunications, vol. 91, pp. 7 – 12, October 2012.

Cite this paper

Ira Tuba, Viktor Tuba. (2018) Node Localization in Wireless Sensor Networks by Water Cycle Algorithm. International Journal of Computers, 3, 91-96

 

cc.png
Copyright © 2018 Author(s) retain the copyright of this article.
This article is published under the terms of the Creative Commons Attribution License 4.0