Ad hoc networks are self-organizing and self-configuring networks that do not have fixed infrastructures. Mobile stations in wireless ad hoc networks move around in the network, thus requiring routing to dynamically handle the constant changing of network topologies. In this paper, we propose a fuzzy logic-based on-demand routing protocol (FBRP) for mobile ad hoc networks. The FBRP selects routes based on power of battery and speed of mobile nodes. The results of simulation and a comparison of the proposed method with the well-known ad hoc on-demand distance vector protocol revealed better performance and a higher fault tolerance for our approach, particularly in terms of node failures.
This is a preview of subscription content, access via your institution.
Buy single article
Instant access to the full article PDF.
Tax calculation will be finalised during checkout.
Subscribe to journal
Immediate online access to all issues from 2019. Subscription will auto renew annually.
Tax calculation will be finalised during checkout.
Raich, A., Vidhate, A.: Best path finding using location aware AODV for MANET. Int. J. Adv. Comput. Res. 3, 336–340 (2013)
Brahma, M., Kim, K.W., Abouaissa, A., Lorenz, P.: A load-balancing and push-out scheme for supporting QOS in MANETs. Telecommun. Syst. 30, 161–175 (2005)
Tabatabaei, S., Teshnehlab, M., Mirabedini, S.J.: A new routing protocol to increase throughput in mobile ad hoc networks. Wireless Pers. Commun. 83, 1765–1778 (2015)
EL-Afandi, H.: An intelligent wireless ad hoc routing protocol. University of Wisconsin_Milwaukee (2006)
You, L., Li, J., Wei, C., Dai, C., Xu, J., Hu, L.: A hop count based heuristic routing protocol for mobile delay tolerant networks. Sci. World J. (2014)
Moussaoui, A., Semchedine, F., Boukerram, A.: A link-state QoS routing protocol based on link stability for mobile ad hoc networks. J. Netw. Comput. Appl. 39, 117–125 (2014)
Tabatabaei, Sh., Teshnehlab, M., Mirabedini, S.J.: Fuzzy-based routing protocol to increase throughput in mobile ad hoc networks. Wireless Pers. Commun. 84, 2307–2325 (2015)
Lin, G.T.R., Lin, Ch., Chou, C.J., Lee, YCh.: Fuzzy modeling for information security management issues in cloud computing. Int. J. Fuzzy Syst. 16, 529–540 (2014)
Jeng, J.T., Chuang, Ch., Tseng, Ch., Juan, ChJ: Robust interval competitive agglomeration clustering algorithm with outliers. Int. J. Fuzzy Syst. 12, 227–236 (2010)
Tsai, Ch., Chen, Ch., Chan, Ch., Li, Y.: Behavior-based navigation using heuristic fuzzy kohonen clustering network for mobile service robots. Int. J. Fuzzy Syst. 12, 25–32 (2010)
Baklizi, M., Abdel-Jaber, H., Shareha, A.A., Abualhaj, M.M., Ramadass, S.: Fuzzy logic controller of gentle random early detection based on average queue length and delay rate. Int. J. Fuzzy Syst. 16, 9–19 (2014)
Shafigh, A.S., Abdollahi, K., Kouchaki, M.: Developing a fuzzy logic based on demand multicast routing protocol. J. Electr. Comput. Eng. 2012, 1–14 (2012)
Nie, J., Wen, J., Luo, J., He, X., Zhou, Z.: An adaptive fuzzy logic based secure routing protocol in mobile ad hoc networks. Wireless Network Lab, Beijing University of Posts and Telecommunications, China, 2006
Gupta, S., Bharti, P.K., Choudhary, V.: Fuzzy logic based routing algorithm for mobile ad hoc networks. In: High Performance Architecture and Grid Computing Communications in Computer and Information Science, vol. 169, pp. 574–579 (2011)
Vu T.K., Kwon, S.: Mobility-assisted on-demand routing algorithm for MANETs in the presence of location errors. Sci. World J. (2014)
Sivakumar, B., Bhalaji, N., Sivakumar, D.: A survey on investigating the need for intelligent power-aware load balanced routing protocols for handling critical links in MANETs. Sci. World J. (2014)
Sumathia, K., Priyadharshinib, A.: Energy optimization in MANETS using on demand routing protocol. Proc. Comput. Sci. 47, 460–470 (2015)
Kumar, K., Singh, V.P.: Power consumption based simulation model for mobile ad-hoc network. Wireless Pers. Commun. 77, 1437–1448 (2014)
Saraireh, M., Saatchi, R., Al-khayatt, S., Strachan, R.: Assessment and Improvement of Quality of Service in Wireless Networks Using Fuzzy and Hybrid Genetic-Fuzzy Approaches. Springer, Berlin (2008)
Mirabedini, S.J., Teshnehlab, M., Shenasa, S.H., Rahmani, A.M.: FLAR: an adaptive fuzzy routing algorithm for communications networks using mobile ants. Int. J.-Cybern. Syst. 39, 684–702 (2008)
Ning, P., Sun, K.: How to misuse AODV: a case study of insider attacks against mobile ad-hoc routing protocols. Cyber Defense Laboratory, Computer Science Department, North Carolina State University, Raleigh (2004)
OPNET Modeler. http://www.opnet.com
Broch, J., Maltz, D.A., Johnson, D.B., Hu, Y., Jetcheva, J.: A performance comparison of multi-hop wireless ad hoc network routing protocols. In: International Conference on Mobile Computing and Networking, pp. 85–97, New York (1998)
Michiardi, P., Molva, R.: Simulation-based analysis of security exposures in mobile ad hoc networks. In: Proceedings of European Wireless Conference (2002)
Wang, N.-C., Huang, Y.-F., Chen, J.-C.: A Stable Weight-Based on-Demand Routing Protocol for Mobile Ad Hoc Networks. Elsevier Inc, Amsterdam (2007)
About this article
Cite this article
Tabatabaei, S., Hosseini, F. A Fuzzy Logic-Based Fault Tolerance New Routing Protocol in Mobile Ad Hoc Networks. Int. J. Fuzzy Syst. 18, 883–893 (2016). https://doi.org/10.1007/s40815-015-0119-z
- Mobile ad hoc networks
- Stable route
- Fuzzy logic
- Ad hoc protocol