ENHANCEMENT OF VoIP PERFROMANCE IN MANET USING FUZZY LOGIC
Voiceover Internet Protocol (VoIP) application is a vital technology that is quickly growing in the Mobile Ad hoc NETwork (MANET). Packet loss is a factor that can significantly affect the Quality of Service (QoS) for VoIP performance. Due to the dynamic nature of MANET, it is a challenging task to maintain the desired packet loss rate. This paper aims to enhance the performance of VoIP in the MANET using a fuzzy logic model. The input for the model is VoIP packet loss and the outputs are the optimal parameters of MANET (node number, pause time, maximum speed, and maximum connection).Network Simulator (NS2) was used to perform all simulations. MATLAB was used to implement the proposed fuzzy model. Moreover, the performance of the model was evaluated using NS2, and the results show that our proposed fuzzy model offers a significant enhancement in terms of the VoIP packet loss rate (P.LR).
S. Na and S. Yoo, "Allowable propagation delay for VoIP calls of acceptable quality," in International Workshop on Advanced Internet Services and Applications, 2002, pp. 47-55.
T.-K. Chua and D. C. J. I. N. Pheanis, "QoS evaluation of sender-based loss-recovery techniques for VoIP," Vol. 20, No. 6, 2006, pp. 14-22.
U. Varshney, A. Snow, M. McGivern, and C. J. C. o. t. A. Howard, "Voice over IP," Vol. 45, No. 1, 2002, pp. 89-96.
W. Wang, S. C. Liew, and V. O. J. I. t. o. v. t. Li, "Solutions to performance problems in VoIP over a 802.11 wireless LAN," Vol. 54, No. 1, 2005, pp. 366-384.
A. A. Yahya and M. A. Alhanish, "Study the Effect of OSPF and IS-IS Protocols Convergence on the VoIP Performance."
Y. Tanaka, "An overview of fuzzy logic," Proceedings of WESCON'93, 1993, pp. 446-450.
M. E. Ebrahim and H. A. Hefny, "Fuzzy Logic based Approach for VoIP Quality Maintaining," International Journal Of Advanced Computer Science And Applications, Vol. 9, No. 1, 2018, pp. 537-542.
S. Ballı and M. Tuker, "A fuzzy multi-criteria decision analysis approach for the evaluation of the network service providers in Turkey," Intelligent Automation & Soft Computing, 2017, pp. 1-7.
S. Jain and M. Chawla, "A fuzzy logic based buffer management scheme with traffic differentiation support for delay tolerant networks," Telecommunication Systems, Vol. 68, No. 2, 2018, pp. 319-335.
K. Kumar, K. Narayana, and B. Sangmitra, "Congestion control in high speed networks using fuzzy logic control," International Journal of Mathematics and Soft Computing, Vol. 5, No. 1, 2015, pp. 45-55.
J. Li, L. Yang, X. Fu, F. Chao, and Y. Qu, "Dynamic QoS solution for enterprise networks using TSK fuzzy interpolation," IEEE International Conference on Fuzzy Systems, 2017, pp. 1-6.
N. K. Quoc, V. T. Tu, and N. T. Hai, "Some Improvements on Active Queue Management Mechanism Based on Adaptive Fuzzy Control," EAI Endorsed Transactions on Context-aware Systems & Applications, Vol. 2, No. 6, 2015, p. e4.
T. Mekni, K. IbnTaarit, and M. Ksouri, "Adaptive neuro-fuzzy interence system congestioi detection protocol," International Conference on Advanced Systems and Electric Technologies, 2018, pp. 363-3680.
A. Salama, R. Saatchi, and D. Burke, "Fuzzy Logic and Regression Approaches for Adaptive Sampling of Multimedia Traffic in Wireless Computer Networks," Technologies, Vol. 6, No. 1, 2018, pp. 24.
T. P. Venkatesan, P. Rajakumar, and A. Pitchaikkannu, "Overview of Proactive Routing protocols in MANET," Fourth International Conference on Communication Systems and Network Technologies, 2014, pp. 173-177.
W. Mansouri, K. B. Ali, F. Zarai, and M. S. Obaidat, "Radio resource management for heterogeneous wireless networks: Schemes and simulation analysis," Modeling and Simulation of Computer Networks and Systems, 2015, pp. 767-792.
E. Kayacan, A. Sarabakha, S. Coupland, R. John, and M. A. J. E. A. o. A. I. Khanesar, "Type-2 fuzzy elliptic membership functions for modeling uncertainty," Vol. 70, 2018, pp. 170-183
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