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Heidari, Ehsan, Motameni, Homayun, Movaghar, Ali. (1400). A meta-heuristic clustering method to reduce energy consumption in Internet of things. نشریه تخصصی هنرهای کاربردی, 12(1), 45-58. doi: 10.22075/ijnaa.2021.4657
Ehsan Heidari; Homayun Motameni; Ali Movaghar. "A meta-heuristic clustering method to reduce energy consumption in Internet of things". نشریه تخصصی هنرهای کاربردی, 12, 1, 1400, 45-58. doi: 10.22075/ijnaa.2021.4657
Heidari, Ehsan, Motameni, Homayun, Movaghar, Ali. (1400). 'A meta-heuristic clustering method to reduce energy consumption in Internet of things', نشریه تخصصی هنرهای کاربردی, 12(1), pp. 45-58. doi: 10.22075/ijnaa.2021.4657
Heidari, Ehsan, Motameni, Homayun, Movaghar, Ali. A meta-heuristic clustering method to reduce energy consumption in Internet of things. نشریه تخصصی هنرهای کاربردی, 1400; 12(1): 45-58. doi: 10.22075/ijnaa.2021.4657

A meta-heuristic clustering method to reduce energy consumption in Internet of things

International Journal of Nonlinear Analysis and Applications
مقاله 5، دوره 12، شماره 1، مرداد 2021، صفحه 45-58    اصل مقاله (379.54 K)
نوع مقاله: Research Paper
شناسه دیجیتال (DOI): 10.22075/ijnaa.2021.4657
نویسندگان
Ehsan Heidari1؛ Homayun Motameni* 1؛ Ali Movaghar2
1Department of Computer Engineering, Sari Branch, Islamic Azad University, Sari, Iran
2Department of Computer Engineering, Sharif University of Technology, Tehran, Iran
تاریخ دریافت: 07 اردیبهشت 1399،  تاریخ بازنگری: 05 آبان 1399،  تاریخ پذیرش: 09 آبان 1399 
چکیده
The Internet of Things (IoT) is an emerging phenomenon in the field of communication, in which smart objects communicate with each other and respond to user requests. The IoT provides an integrated framework providing interoperability across various platforms. One of the most essential and necessary components of IoT is wireless sensor networks. Sensor networks play a vital role in the lowest level of IoT. Sensors in sensor networks use batteries which are not replaceable, and hence, energy consumption becomes of great importance. For this reason, many algorithms have been recently proposed to reduce energy consumption. In this paper, a meta-heuristic method called whale optimization algorithm(WOA) is used to clustering and select the optimal cluster head in the network. Factors such as residual energy, shorter distance, and collision reduction have been considered to determine the optimal cluster head. To prove the optimal performance of the proposed method, it is simulated and compared with three other methods in the same conditions. It outperforms the other methods in terms of energy consumption and the number of dead nodes.
کلیدواژه‌ها
Internet of Things؛ clustering؛ routing؛ energy consumption؛ whale optimization algorithm
مراجع

[1] K. Ashton, That “Internet of Things” Thing. RFID Journal 22 (2009) 97–114.

[2] L. Atzori, A. Iera, and G. Morabito, The Internet of things: A survey, Computer networks 54(15) (2010) 2787-2805.

[3] D. Chemodanov, F. Esposito, A. Sukhov, P. Calyam, H.Trinh, Z. Oraibi, AGRA: AI-augmented geographic routing approach for IoT-based incident-supporting applications, Future Generation Computer Systems  92 (2019) 1051-1065.

[4] F. Safara, A. Souri, T. Baker, I. Al Ridhawi, M. Aloqaily, Prinergy: a priority-based energy-efficient routing method for IoT systems, The Journal of Supercomputing (2020) 1-8.

[5] B.D. Deebak and F. Al-Turjman, A hybrid secure routing and monitoring mechanism in IoT-based wireless sensor networks. Ad Hoc Networks 97 (2020) 102022.

[6] K. Majumder, S. Ray, and S.K. Sarkar, A novel energy efficient chain based hierarchical routing protocol for wireless sensor networks, INTERACT-2010, IEEE, 2010, Dec 3, pp. 339-344.

[7] T. Muhammed, R. Mehmood, A. Albeshri, and A. Alzahrani, HCDSR: A hierarchical clustered fault-tolerant routing technique for IoT-based smart societies, Smart Infrastructure and Applications, Springer, Cham., 2020, pp. 609-628.

[8] S. Kumar, V.K. Solanki, S.K. Choudhary, A. Selamat, and R. González Crespo, Comparative Study on Ant Colony Optimization (ACO) and K-Means Clustering Approaches for Jobs Scheduling and Energy Optimization Model in Internet of Things (IoT), International Journal of Interactive Multimedia & Artificial Intelligence 6(1) (2020).

[9] J. Shen, A. Wang, C. Wang, P.C. Hung, and C.F. Lai, An efficient centroid-based routing protocol for energy management in WSN-assisted IoT, IEEE Access 5 (2017), 18469-18479.

[10] N. Javaid, S. Cheema, M. Akbar, N. Alrajeh, M.S. Alabed, and N. Guizani, Balanced energy consumption based adaptive routing for IoT enabling underwater WSNs, IEEE Access 19 (2017) 10040-10051.

[11] D. Chemodanov, F. Esposito, A. Sukhov, P. Calyam, H. Trinh, and Z. Oraibi, AGRA: AI-augmented geographic routing approach for IoT-based incident-supporting applications, Future Generation Computer Systems 92 (2019) 1051-1065.

[12] Y. Jin Y, S. Gormus, P. Kulkarni, and M. Sooriyabandara, Content-centric routing in IoT networks and its integration in RPL. Computer Communications 89 (2016 ) 87-104.

[13] S.A. Chelloug, Energy-efficient content-based routing in the Internet of things, Journal of Computer and Communications 3(12) (2015) 9.

[14] X. Jia, Q.  Feng, T. Fan, and Q. Lei, RFID technology and its applications in Internet of Things (IoT), 2nd international conference on consumer electronics, communications and networks (CECNet) 2012, pp. 1282-1285.

[15] M. Sajwan, D. Gosain, A.K. Sharma, CAMP: cluster aided multi-path routing protocol for wireless sensor networks. Wireless Networks 25(5) (2019) 2603-2620.

[16] M. Pant, B. Dey B, and S. Nandi, A multihop routing protocol for wireless sensor network based on grid clustering, Applications and Innovations in Mobile Computing (AIMoC), 2015 Feb 12, pp. 137-140.

[17] W.B. Heinzelman, A.P. Chandrakasan, and H. Balakrishnan, An application-specific protocol architecture for wireless microsensor networks. IEEE Transactions on Wireless Communications. 1(4) (2002) 660-670.

[18] M.M. Ahmed, E.H. Houssein, A.E. Hassanien, A.Taha, and E. Hassanien, Maximizing lifetime of wireless sensor networks based on whale optimization algorithm, International conference on advanced intelligent systems and informatics, Springer, Cham., 2017 Sep 9, pp. 724-733.

[19] T.A. Al-Janabi and H.S. Al-Raweshidy, Efficient whale optimisation algorithm-based SDN clustering for IoT focused on node density. In2017 16th Annual Mediterranean Ad Hoc Networking Workshop (Med-Hoc-Net) 2017 Jun 28, pp. 1-6.

[20] V. Anand and S. Pandey, New approach of GA–PSO‐based clustering and routing in wireless sensor networks, International Journal of Communication Systems, 2020 Aug; e457.

[21] W.A. Altakhayneh, M. Ismail, M.A. Altahrawi, and M.K. AbuFoul, Cluster Head Selection Using Genetic Algorithm in Wireless Network, IEEE 14th Malaysia International Conference on Communication (MICC) 2019 Dec 2, pp. 13-18.

[22] E. Heidari and A. Movaghar, An efficient method based on genetic algorithms to solve sensor network optimization problem, arXiv preprint arXiv:1104.0355. 2011 Apr 3.

[23] N. Muruganantham and H. El-Ocla, Routing using genetic algorithm in a wireless sensor network, Wireless Personal Communications (2020) 1-30.

[24] S. Mirjalili, A. Lewis, The whale optimization algorithm, Advances in engineering software 95 (2016) 51-67. 

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