Subject Areas : Majlesi Journal of Telecommunication Devices

Shayeseteh Tabatabaei ¹ , Bager Bahram Shotorban ²

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Received: 2025-11-15 Accepted : 2025-12-07 Published : 2025-12-09

Keywords:

References:

[1] J. Yick et al., “Wireless sensor network survey,” Comput. Netw., vol. 52, no. 12, pp. 2292–2330, 2008.

[2] M. A. Alsheikh et al., “Mobile big data analytics using deep learning and Apache Spark,” IEEE Netw., vol. 30, no. 3, pp. 22–29, 2016.

[3] V. Potdar et al., “Energ.y-efficient protocols for wireless sensor networks: A survey,” IEEE Commun. Surveys Tuts., vol. 11, no. 4, pp. 97–114, 2009.

[4] A. A. Abbasi et al., “A survey on clustering algorithms for wireless sensor networks,” Comput. Commun., vol. 30, no. 14–15, pp. 2826–2841, 2007.

[5] X. Liu, “A survey on clustering routing protocols in wireless sensor networks,” Sensors, vol. 12, no. 8, pp. 11113–11153, 2012.

[6] S. Arjunan et al., “Lifetime maximization of wireless sensor network using fuzzy-based unequal clustering and ACO,” Ad Hoc Netw., vol. 73, pp. 1–16, 2018.

[7] J. Wang et al., “Fuzzy-logic-based clustering approach for wireless sensor networks using energy predication,” IEEE Sensors J., vol. 22, no. 10, pp. 10053–10063, 2022.

[8] R. Tang et al., “A multi-objective genetic algorithm for optimizing energy consumption in cluster-based wireless sensor networks,” IEEE Internet Things J., vol. 10, no. 5, pp. 4125–4138, 2023.

[9] Capello, F., Toja, M., & Trapani, N. (2016). A real-time monitoring service based on industrial internet of things to manage agrifood logistics. In Proceedings of the 6th International Conference on Information Systems, Logistics and Supply Chain, Bordeaux, France, Available from: http://ils2016conference. com/wpcontent/uploads/2015/03/ILS2016_FB01_1. pdf, Accessed (pp. 10-21).
‏
[10] Pang, Z., Chen, Q., Han, W., & Zheng, L. (2015). Value-centric design of the internet-of-things solution for food supply chain: Value creation, sensor portfolio and information fusion. Information Systems Frontiers, 17(2), 289-319.
‏
[11] Kumar, A., Shwe, H., Wong, K., & Chong, P. (2017). Location-based routing protocols for wireless sensor networks: a survey. Wireless Sens. Netw. 9, 25–72 (2017).
‏
[12] Lin, K., Chen, M., Zeadally, S., & Rodrigues, J. J. (2012). Balancing energy consumption with mobile agents in wireless sensor networks. Future Generation Computer Systems, 28(2), 446-456.
‏
[13] Ferng, H. W., Tendean, R., & Kurniawan, A. (2012). Energy-efficient routing protocol for wireless sensor networks with static clustering and dynamic structure. Wireless Personal Communications, 65(2), 347-367.
‏
[14] Papadopoulos, A., Navarra, A., McCann, J. A., & Pinotti, C. M. (2012). VIBE: An energy efficient routing protocol for dense and mobile sensor networks. Journal of Network and Computer Applications, 35(4), 1177-1190.
‏
[15] Han, S. W., Jeong, I. S., & Kang, S. H. (2013). Low latency and energy efficient routing tree for wireless sensor networks with multiple mobile sinks. Journal of Network and Computer Applications, 36(1), 156-166.
‏
[16] Abasıkeleş-Turgut, İ., & Hafif, O. G. (2016). NODIC: a novel distributed clustering routing protocol in WSNs by using a time-sharing approach for CH election. Wireless Networks, 22(3), 1023-1034.
‏
[17] Gajjar, S., Sarkar, M., & Dasgupta, K. (2016). FAMACROW: Fuzzy and ant colony optimization based combined mac, routing, and unequal clustering cross-layer protocol for wireless sensor networks. Applied Soft Computing, 43, 235-247.

[18] Shokouhifar, M., & Jalali, A. (2015). A new evolutionary based application specific routing protocol for clustered wireless sensor networks. AEU-International Journal of Electronics and Communications, 69(1), 432-441.
‏
[19] Tabatabaei, S., Rajaei, A., & Rigi, A. M. (2019). A novel energy-aware clustering method via Lion Pride Optimizer Algorithm (LPO) and fuzzy logic in wireless sensor networks (WSNs). Wireless Personal Communications, 108(3), 1803-1825.
‏
[20] Shelebaf, A., & Tabatabaei, S. (2020). A Novel Method for Clustering in WSNs via TOPSIS Multi-criteria Decision-Making Algorithm. Wireless Personal Communications, 1-17.
‏
[21] Akbari, Y., & Tabatabaei, S. A New Method to Find a High Reliable Route in IoT by Using Reinforcement Learning and Fuzzy Logic. Wireless Personal Communications, 1-17.
‏
[22] Nikolidakis, S. A., Kandris, D., Vergados, D. D., & Douligeris, C. (2015). Energy efficient automated control of irrigation in agriculture by using wireless sensor networks. Computers and Electronics in Agriculture, 113, 154-163.
‏
[23] Polo, J., Hornero, G., Duijneveld, C., García, A., & Casas, O. (2015). Design of a low-cost wireless sensor network with UAV mobile node for agricultural applications. Computers and electronics in agriculture, 119, 19-32.
‏
[24] Tabatabaei, S. (2022). Provide energy-aware routing protocol in wireless sensor networks using bacterial foraging optimization algorithm and mobile sink. PloS one, 17(3), e0265113.

[25] Fanian, F., & Rafsanjani, M. K. (2020). A new fuzzy multi-hop clustering protocol with automatic rule tuning for wireless sensor networks. Applied Soft Computing, 89, 106115.

[26] Maurya, S., Jain, V. K., & Chowdhury, D. R. (2019). Delay aware energy-efficient reliable routing for data transmission in heterogeneous mobile sink wireless sensor network. Journal of Network and Computer Applications, 144, 118-137.
‏
[27] Gorgich, S., & Tabatabaei, S. (2021). Proposing an energy-aware routing protocol by using fish swarm optimization algorithm in WSN (wireless sensor networks). Wireless Personal Communications, 119(3), 1935-1955.

[28] Ergun, K., Ayoub, R., Mercati, P., & Rosing, T. (2022). Reinforcement learning based reliability-aware routing in IoT networks. Ad Hoc Networks, 132, 102869.

[29] Feroz Khan, A. B., & CN, R. (2022). A multi-attribute based trusted routing for embedded devices in MANET-IoT.

[30] Tabatabaei, S., & Rigi, A. M. (2019). Reliable routing algorithm based on clustering and mobile sink in wireless sensor networks. Wireless Personal Communications, 108(4), 2541-2558.

[31] OPNET Modeler, Available from: http://www.opnet.com.

[32] DCRRP PROTOCOL Standard-2003, “Part 15.4: Wireless Medium Access Control (MAC) and Physical Layer (PHY) Specifications for Low-Rate Wireless Personal Area Networks (LR-WPANs)”, IEEE-SA Standards.