[1] M. Sudip, W. Isaac, M. Subhas Chandra, Guide to wireless sensor networks, Computer Communication and Network Series, Springer, London, 2009.
[2] M. Zawodniok and S. Jagannathan, “Predictive congestion control protocol for wireless sensor networks,” IEEE T. Wirel. Commun., vol. 6, pp. 3955-3963, 2007.
[3] S.S.S. Farahani, “Congestion Control Approaches Applied to Wireless sensor Networks: A Survey,” Journal of Electrical and Computer Engineering Innovations JECEI, vol.6, pp.125-144, 2018.
[4] A. Ghaffari, “Congestion control mechanisms in wireless sensor networks: a survey,” J. Netw., Comput., Appl., vol. 52, pp. 101-115, 2015.
[5] N. Pant, “A comparative study of congestion control in wireless sensor networks using efficient resource management,” presented at the 2nd Int. Conf. Advancement in Engineering, Applied Science and Management (ICAEASM), pp. 320-325, 2017.
[6] S. A. Shah, B. Nazir, and I. A. Khan, “Congestion control algorithms in wireless sensor: trends and opportunities,” J King Saud Univ Sci– Computer and Information Sciences, vol. 29, pp. 236-245, 2017.
[7] M. A. Jan, S. R. U. Jan, M. Alam, A. Akhunzada, and I. Ur Rahman, “A comprehensive analysis of congestion control protocols in wireless sensor networks,” Mobile Netw. Appl., vol. 23, pp. 456–468, 2018.
[8] M. Kaur, V. Verma , and A. Malik , “A comparative analysis of various congestion control schemes in wireless sensor networks,” presented at the 8th International Conference on Cloud Computing, Data Science & Engineering (Confluence), Noida, India, 2018.
[9] B. Nawaz, K. Mahmood, J. Khan, M.U. Hassan, A. M. Shah, and M. K. Saeed, “Congestion control techniques in wsns: a review,” Int J Adv Comput Sci Appl (IJACSA), vol. 10, pp. 194-199, 2019.
[10] C. Sergiou, P. Antoniou, V. Vassiliou, “Congestion Control Protocols in Wireless Sensor Networks: A Survey,” IEEE Commun. Surv. Tutorials,vol.16, pp.1839 - 1859, 2014.
[11] N. Thrimoorthy and T. Anuradha, “Congestion detection approaches in wireless sensor networks: a comparative study,” Int J Eng Sci Res DEV, vol. 12, pp. 59-63, 2016.
[12] A. M. Ahmed and R. Paulus, “Congestion detection technique for multipath routing and load balancing in WSN,” Wireless Netw., vol. 23, pp. 881–888, 2017.
[13] C. Chrysostomou, A. Pitsillides, Fuzzy Logic Control in Communication Networks, Foundation of Computational Intelligence, Vol.2, pp.197-236, Springer International Publishing, 2009.
[14] M. Ghalehnoie, N. Yazdani, and F. R. Salmasi, “Fuzzy rate control in wireless sensor networks for mitigating congestion” presented at the International Symposium on Telecommunications, pp. 312–317, Tehran, Iran, 2008.
[15] M. Zarei, A. M. Rahmani, R. Farazkish, “CCTF: congestion control protocol based on trustworthiness of nodes in wireless sensor networks using fuzzy logic,” Int. J. Ad Hoc Ubiquitous Comput., vol.8, pp. 54–63, 2011.
[16] S. A. Munir, W. B. Yu, B. Ren, and M. Ma. “Fuzzy logic-based congestion estimation for qos in wireless sensor network,” presented at the Wireless Communications and Networking Conference (WCNC 07), pp. 4336–4341, 2007.
[17] J. Sayyada and N. K. Choudhari, “Hierarchical tree-based congestion control using fuzzy logic for heterogeneous traffic in wsn,” International Journal of Current Engineering and Technology, vol.4, pp. 4136–4143, 2014.
[18] F. Pasandideh and A. A. Rezaee, “A fuzzy priority based congestion control scheme in wireless body area networks,” Int. J. of Wireless and Mobile Computing, vol.14, p. 1-15, 2018.
[19] P. Aimtongkham, T. G. Nguyen, and C. So-In, “Congestion control and prediction schemes using Fuzzy logic system with adaptive membership function in wireless sensor networks,” Wirel Commun Mob Comput, pp. 1-19, 2018.
[20] A. A. Rezaee and F. Pasandideh, “A fuzzy congestion control protocol based on active queue management in wireless sensor networks with medical applications,” Wireless Pers. Commun., vol. 98, pp. 815–842, 2018.
[21] S. Qu, L. Zhao, Z. Xiong, “Cross-layer congestion control of wireless sensor networks based on fuzzy sliding mode control,” Neural Comput and Applic, vol. 32, pp. 13505–13520, 2020.
[22] J. Wei, B. Fan, and Y. Sun, “A congestion control scheme based on fuzzy logic for wireless sensor networks,” presented at the 9th Int. Conf. Fuzzy Systems and Knowledge Discovery, pp. 501–504, 2012.
[23] K. Mekathoti Vamsi, B. Nithya, “Network Status Aware Congestion Control (NSACC) Algorithm for Wireless Body Area Network,” Procedia Comput Sci, vol. 171, pp. 42-51, 2020.
[24] R. Chakravarthi, C. Gomathy, “IFCCDC: A Fuzzy control based Congestion Detection and Control in Wireless Sensor Networks”, Int J Comput Appl, vol.47, 2012.
[25] C. Basaran, K.D. Kang, and M. H. Suzer “Hop-by-Hop Congestion Control and Load Balancing in Wireless Sensor Networks” presented at the IEEE Local Computer Network Conference, Denver, CO, USA, 2010.
[26] M. Samimi, A. Rezaee, and M. H. Yaghmaee, “Design a new fuzzy congestion controller in wireless sensor networks,” Int. J. Inf. Electron. Eng., vol.2, 395–399, 2012.
[27] S. Jaiswal and A. Yadav, “Fuzzy based adaptive congestion control in wireless sensor networks,” presented at the Sixth International Conference on Contemporary Computing, pp. 433-438, 2013.
[28] Y. L. Chen and H. P. Lai, “Priority-based transmission rate control with a fuzzy logical controller in wireless multimedia sensor networks,” Comput Math Appl, vol. 64, pp. 688-698, 2012.
[29] K. Hausken and J. Zhuang (Eds.), Game Theoretic Analysis of Congestion, Safety and Security, Springer Series in Reliability Engineering, Springer International Publishing Switzerland, 2015.
[30] R. Garg, A. Kamra, and V. Khurana, “A game-theoretic approach towards congestion control in communication networks,” ACM SIGCOMM Computer Communication Review, vol.32, pp.47-61, 2002.
[31] N. Farzaneh, and M.H. Yaghmaee, “An adaptive competitive resource control protocol for alleviating congestion in wireless sensor networks: an evolutionary game theory approach,” Wirel Pers Commun, vol.82, pp.123-142, 2015.
[32] C. Ma, J. P Sheu, and C. X. Hsu, “A game theory-based congestion control protocol for wireless personal area networks,” Hindawi Publishing Corporation, J Sens, pp.1-16, 2016.
[33] J. Hu, Q. Qian, A. Fang, S.Wu, and Y. Xie, “Optimal data transmission strategy for health care based wireless sensor networks: A stochastic differential game approach,” Wirel Pers Commun, vol. 89, pp.1295–1313, 2016.
[34] E. Altman, R. El-Azouzi, Y. Hayel, H. Tembine, “An evolutionary game approach for the design of congestion control protocols in wireless networks,” presented at the Physicomnet Workshop, Berlin, April 4, 2008.
[35] Blum, Christian, Merkle, Daniel (Eds.), Swarm Intelligence, Introduction and Applications, Neural Computing series, Springer International Publishing 2008.
[36] V. Senniappan, J. Subramanian, and A. Thirumal, “Application of novel swarm intelligence algorithm for congestion control in structural health monitoring,” presented at the IEEE Region 10 Conference (TENCON) , pp. 24–27, 2016.
[37] K. Singh, K. Singh, L. Hoang Son, and A. Aziz, “Congestion control in wireless sensor networks by hybrid multi-objective optimization algorithm,” Comput. Netw., vol. 138, pp. 90-107, 2018.
[38] P. Antoniou, A. Pitsillides, T. Blackwell, A. Engelbrech, L. Michael, “Congestion control in wireless sensor networks based on bird flocking behaviour,” Comput. Netw., vol.57, pp.1167–1191, 2013.
[39] V. E. Narawade and U. D. Kolekar, “Eacsro: epsilon constraint-based adaptive cuckoo search algorithm for rate optimized congestion avoidance and control in wireless sensor networks,” presented at the International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC), pp. 715–720, 2017.
[40] M. S. Manshahia, M. Dave, and S. B. Singh, “Computational intelligence for congestion control and quality of service improvement in wireless sensor networks,” Transactions on Machine Learning and artificial Intelligence, vol.5, pp.21-35, 2017.
[41] M. Royyan, M. Rusyadi Ramli , J. M.Lee , and D. S. Kim, “Bio-inspired scheme for congestion control in wireless sensor networks,” presented at the 14th IEEE International Workshop on Factory Communication Systems (WFCS), pp. 1 – 4, 2018.
[42] M. S. Manshahia, M. Dave, and S. B.Singh, “Improved bat algorithm based energy efficient congestion control scheme for wireless sensor networks,” Wireless Sensor Network, vol. 8, pp. 229-241, 2016.
[43] L. Lin, Y. Shi, J. Chen, and S. Ali, “A Novel Fuzzy PID Congestion Control Model Based on Cuckoo Search in WSNs,” Sensors (Basel), vol.20, 2020.
[44] A. Rezvanian, A.M. Saghiri, S.M. Vahidipour, M. Esnaashari, M.R. Meybodi, Recent Advances in Learning Automata, studies in computational studies, Springer International Publishing, 2018.
[45] P. Moghiseh and A. Heydari, “Congestion control in wireless sensor networks using learning automata,” International Journal of Computer Science and Wireless Network, vol. 3, pp. 157-165, 2018.
[46] N.F. Bahalgardi, M. H. Yaghmaee, and D. Adjeroh, “An adaptive congestion alleviating protocol for healthcare applications in wireless body sensor networks: learning automata approach,” Amirkabir International Journal of Electrical and Electronics Engineering, vol. 44 , pp. 31-41, 2012.
[47] S. A. Chelloug, “An intelligent closed-loop learning automaton for real-time congestion control in wireless body area networks,” Int. J. Sensor Networks, vol. 26, pp. 190-199, 2018.
[48] M.H. Yaghmaee, N.F. Bahalgardi, and D. Adjeroh, “A prioritization based congestion control protocol for healthcare monitoring application in wireless sensor networks,” Wirel Pers Commun, vol. 72, pp.2605–2631, 2013.
[49] S. Misra, V. Tiwari, and M. S. Obaidat, “Lacas: learning automata-based congestion avoidance scheme for health care wireless sensor networks,” IEEE J. Sel. Areas Commun., vol. 27, pp. 466–479, 2009.
[50] R. Hashemzehi, “A learning automata-based protocol for solving congestion problem in wireless sensor network,” International Journal of Emerging Trends and Technology in Computer Science, vol. 2, pp. 396-399, 2013.
[51] A.A. Rezaee, M.H. Yaghmaee, and A.M. Rahmani, “Optimized congestion management protocol for healthcare wireless sensor networks,” Wirel Pers Commun, vol. 75, pp.11–34, 2014.
[52] K. Hotnik, M. Stinchcombe, and H. White, “Multilayer Feedforward Networks are Universal Approximators,” NEURAL NETW, vol.2, pp.359-366, 1989.
[53] A. A. Tarraf, I. W. Habib, and T. N. Saadawi, “Intelligent trafEc control for ATM Broadband Networks,” IEEE Commun Mag, vo1.33, pp.76-85, 1995.
[54] X. Yang, X. Chen, R. Xia , Z. Qian , “Wireless sensor network congestion control based on standard particle swarm optimization and single neuron PID,” Sensors (Basel), vol. 18, 2018.
[55] V. E. Narawade, U. D. Kolekar, “NNRA-CAC: NARX Neural Network-based Rate Adjustment for Congestion Avoidance and Control in Wireless Sensor Networks,” NEW REV INF NET, vol. 22, pp. 85–110, 2017.
[56] H. Mollaei, A. A. Emrani Zarandi, “New Method for Congestion Control in Wireless Sensor Network Using Neural Network,” QUID: Investigacion, ciencia y tecnologia, Institucion Universitaria Salazar y Herrera, IUSH, pp. 1085-1093, 2017.
[57] X. Jin, Y. Yang, J. Ma, Z. Li, “Congestion Control of Wireless Sensor Networks based on L1/2 Regularization,” presented at the Chinese Control And Decision Conference (CCDC), 2019.
[58] M. A. Hussain, “A Radial Basis Neural Network Controller to Solve Congestion in Wireless Sensor Networks,” Iraqi Journal for Computers and Informatics (IJCI), vol. 44, 2018.
[59] N. A. Shiltagh , Z. G. Faisal, “Traffic Management in Wireless Sensor Network Based on Modified Neural Networks,” Iraqi Journal for Computers and Informatics (IJCI), vol.1, 2014.