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Performance comparision of different routing protocols with fuzzy inference system in manet

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An ad hoc wireless network consists of mobile networks which create an underlying architecture for communication without the help of traditional fixed-position routers. There are different protocols for handling the routing in the mobile environment. Routing protocols used in fixed infrastructure networks cannot be efficiently used for mobile ad-hoc networks (MANET), so it requires different protocols. The node moves at different speeds in an independent random form, connected by any number of wireless links, where each node is ready to pass or forward both data and control traffic unrelated to its own use ahead (routing) to other nodes in a flexible interdependence of wireless communication in between. In contrast to infrastructure wireless networks, where the communication between network nodes is take place by a special node known as an access point. It is also, in contrast to wired networks in which the routing task is performed by special and specific devices called routers and switches. In this paper, we consider fuzzy inference system, an attempt has been made to present a model using fuzzy logic approach to evaluate and compare three routing protocols i.e. AODV, DSDV and DSR using effective factor of the number of nodes based on 3 outputs of control overhead, delay and PDR (totally fuzzy system with 4 outputs) in order to select one of these two routing protocols properly under different conditions and based on need and goal. To show efficiency and truth of fuzzy system, three protocols have been evaluated equally using NS-2 simulator and attempt has been made to prove efficiency of the designed fuzzy system by comparing results of simulation of fuzzy system and NS-2 software.
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autor
  • Department of IT, Global Group of Institutions, Haldia, Purba Medinipur, WB, India
autor
  • Department of Computer Sciences & Engineerig, Haldia Institute of Technology, Haldia, Purba Medinipur, WB, India
autor
  • Department of Mathematics, Tamralipta Mahabidalay, Tamluk, Purba Medinipur, WB, India
Bibliografia
  • 1. Boukerche A.: Performance evaluation of routing protocols for ad hoc wireless networks. Kluwer Academic Publishers, Netherlands, Mobile Networks and Applications, 9(4), 2004, 333–342.
  • 2. Boukerche A., Bamis A., Chatzigiannakis I., Nikoletseas S.: A mobility aware protocol synthesis for efficient routing in ad hoc mobile networks. The International Journal of Computer and Telecom¬munications Networking, 52(1), 2008, 130–154.
  • 3. Broch J., Maltz A.D., Johnson D.B., Hu Y.C., Jetcheva J.: A performance comparison of multi-hop wireless ad hoc networks. In: Proceedings of the 4th Int. Conjkrence on Mobile Computing and Networking (ACM MOBICOM’98), 1998, 85–97.
  • 4. Broch J., Maltz A.D., Johnson D.B.: The dynamic Source routing protocol for mobile ad hoc networks. lntemet Draft, MANET Working Group, 1999.
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  • 7. Maltz D.A. and Johnson D.B.: Dynamic source routing in ad hoc wireless networks. In: Mobile Computing, Kluwer Academic Publishers, 1996, 153−181.
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  • 9. Maan F. and Mazhar N.: MANET routing protocols vs mobility models: A performance evaluation. In: Proceedings of IEEE, 2011.
  • 10. Lu Y., Wang W., Zhong Y., Bhargava B.: Study of distance vector routing protocols for mobile ad hoc networks. In: Proceedings of the First IEEE International Conference on Pervasive Computing and Communications (PerCom’03), 2003, 187–194.
  • 11. Baumung P., Zitterbart M., Kutzner K.: Improving delivery ratios for application layer multicast in mobile ad-hoc network. Journal of Computer Communication, 28(14), 2005, 1669–1679.
  • 12. Bein D., Datta K.A., Jagganagari R.C., Villain V.: A self-stabilizing link – cluster algorithm in mobile ad hoc networks. In: Proceedings of The International Symposium on Parallel Architectures, Algorithms and Networks (I-SPAN), 4(2), 2005, 436–441.
  • 13. Andlinger P. and Reichl E.R.: Fuzzy-neunet: A non-standard neural network. In: Prieto et al. (Ed.), 1991, 173–180.
  • 14. Arao M., Fukuda T., Shimokima K., Flexible intelligent system based on fuzzy neural networks and reinforcement learning. In: Proceedings of IEEE International Conference on Fuzzy Systems, 5(1), 1995, 69–70.
  • 15. Hayashi Y. and Buckley J.J. Approximations between fuzzy expert systems and neural networks. International Journal of Approximate Reasoning, 10, 1994, 63–73.
  • 16. Bunke H. and Kandel A. Neuro-fuzzy pattern recognition. World Scientific Publishing Co., Singapore 2000.
  • 17. Jelodar H. and Aramideh J.: Comparison AODV and DSDV routing protocols with using fuzzy logic in the MANET. Advances in Science and Technology Research Journal, 8(22), 2014, 19–25.
  • 18. Goswami S. and Das C.B.: Performance analysis of AODV, DSR and DSDV in MANET using NS-2. Global Journal of Computer Science and Information Technology, 1(1), 2014, 75–80.
  • 19. Goswami S., Das C.B., Joardar S.: Performance comparison of routing protocols of MANET using NS-2. Lap Lambert Academic Publishing.
  • 20. Goswami S., Joardar S., Das C.B.: Reactive and proactive routing protocols performance metric comparison in mobile ad hoc networks using NS-2. International Journal of Advanced Research in Computer and Communication Engineering, 3(1), 2014, 4908–4914.
  • 21. Goswami S., Das C.B., Joardar S. Comparative performance analysis of DSDV and AODV routing protocols in MANET using NS-2. Networking and Communication Engineering. 5(12), 2013, 536–544.
Typ dokumentu
Bibliografia
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