Abstract
A mobile ad hoc network is a collection of autonomous mobile nodes having communication capability with one another within a radio range. This is a network with intrinsic attributes like auto-configuration and organization by the network itself. In traditional, AODV single metric is used for the route selection scheme. Here we put forward a stable fuzzy logic-based energy-efficient AODV routing protocol for MANET. This protocol is used for selecting an optimal path to increase network lifetime. Fuzzy logic-based energy-efficient reactive protocol increases the performance metrics by selecting the most trusted node. In the fuzzy logic-based approach, crisp input is fed to the fuzzy inference engine for calculating the most trusted value which can be used as a metric for the route selection. The proposed work is simulated in MATLAB and NS2, and it compares the performance metrics in terms of throughput, end-to-end delay, and packet delivery ratio.
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References
V. Narayan, A.K. Daniel, A novel approach for cluster head selection using trust function in WSN. Scal. Comput. Pract. Exp. 22(1), 1–13 (2021)
A. Gasim, E. Johnson Eric, Fuzzy routing in ad hoc networks, performance, computing, and communications conference 2003. IEEE Int., 525–530 (2003)
G. Santhi, A. Nachiappan, Fuzzy-cost based multi constrained QoS routing with mobility prediction in MAN E Ts. Egypt. Inform. J. 13, 19–25 (2012)
V. Narayan, A.K. Daniel, RBCHS: Region-based cluster head selection protocol in wireless sensor network, in Proceedings of Integrated Intelligence Enable Networks and Computing, (Springer, Singapore, 2021), pp. 863–869
H. Liu, J. Li, Y.-Q. Zhang, Y. Pan, An Adaptive Genetic Fuzzy Multi-path Routing Protocol for Wireless Ad Hoc Networks, International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing and First ACIS International Workshop on Self-Assembling Wireless Networks (SN P DISA WN’05) (2005), pp. 468–475
V. Narayan, A.K. Daniel, A.K. Rai, Energy-efficient two-tier cluster-based protocol for wireless sensor networks, in 2020 International Conference on Electrical and Electronics Engineering (ICE3), (IEEE, 2020, February), pp. 574–579
V. Narayan, A.K. Daniel, Multi-tier cluster-based smart farming using wireless sensor network, in 2020 5th International Conference on Computing, Communication, and Security (ICCCS) (IEEE, 2020, October), pp. 1–5. A. Naga Raju, Dr. S. Ramachandram, Fuzzy cost-based multipath routing for mobile Ad-hoc networks. J. Theoret. Appl. Inform. Technol., 319–326
B. Sun, C. Gui, Q. Zhang, H. Chen, Fuzzy controller based QoS routing algorithm with a multiclass scheme for MANET. Int. J. Comp. Commun. Contl. IV(4), 427–438 (2009) ISSN 1841–9836, E-ISSN 1841–9844
Junwei Wang Zhaoxia Wu, A Fuzzy Decision-Based Intelligent QoS Multicast Routing Algorithm, Automation, and Logistics Conference, Chongqing, China, (August, 2011), pp. 169–172
C. Perkins, E. Belding-Royer, S. Das, Ad hoc on-demand distance vector (AODV) routing. No. RFC 3561 (2003)
X Ban, XZ Gao, X Huang, H Yin, Stability analysis of takagi-sugeno fuzzy control system using circle criterion, in IEEE International Conference on Fuzzy System, (Vancouver, 2006)
F. Dernoncourt, Introduction to Fuzzy Logic, (MIT, Massachusetts 2013)
S. Hadi, A. Barhanaddin, Mohd K. Sabira, A Cross Layer Metrics for Discovery Reliable Route in Mobile Ad hoc Network, (Springer, 2011)
M. Faiz, A.K. Daniel, Fuzzy cloud ranking model based on QoS and trust, in 2020 Fourth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and CL0ud) (I-SMAC), (IEEE, 2020, October), pp. 1051–1057
M. Alreshoodi, E. Danish, J. Woods, A. Fernando, C. De, AL0is. prediction of perceptual quality for mobile video using fuzzy inference system. IEEE Trans. Consum. Electron. 61(4), 546–554 (2015)
J. Liu, O.W.W. Yang, Using Fuzzy Logic control to provide intelligent traffic management service for high-speed networks. IEEE Transac. Netwk. Serv. Manag. 10(2), 148–161 (2013).
M. Alreshoodi, E. Danish, J. Woods, A. Fernando, C. De, ALois. prediction of perceptual quality for mobile video using fuzzy inference system. IEEE Trans. Consum. Electron. 61(4), 546–554 (2015)
J. Liu, O.W.W. Yang, Using fuzzy logic control to provide intelligent traffic management service for high-speed networks. IEEE Trans. Netw. Serv. Manag. 10(2), 148–161 (2013)
V. Narayan, A.K. Daniel, Novel protocol for detection and optimization of overlapping coverage in wireless sensor networks. Int. J. Eng. Adv. Technol. 8 (2019)
V. Narayan, A.K. Daniel, Design consideration and issues in wireless sensor network deployment (2020)
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Choudhary, S., Narayan, V., Faiz, M., Pramanik, S. (2022). Fuzzy Approach-Based Stable Energy-Efficient AODV Routing Protocol in Mobile Ad hoc Networks. In: Ghonge, M.M., Pramanik, S., Potgantwar, A.D. (eds) Software Defined Networking for Ad Hoc Networks. EAI/Springer Innovations in Communication and Computing. Springer, Cham. https://doi.org/10.1007/978-3-030-91149-2_6
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