A Rate based Congestion Control Mechanism Using Fuzzy Controller in MANETs

  • Hamideh Zare
  • Fazlollah Adibnia yazd university
  • Vali Derhami yazd university

Abstract

The traditional congestion control mechanism TCP, performs very poorly in MANETs Because there are a number of new challenges such as wireless link error, medium contention and frequent route failures in this kind of networks. In this paper, we propose a fuzzy adhoc rate-based congestion control (FARCC) to enhance the efficiency of network in MANETs. In FARCC, we use a rate-based transmission scheme using two fuzzy controller of zero order Takagi Sugeno Kang (TSK) model to congestion detection and congestion control. The FARCC sender adjusts data rate by receiving a feedback packet from FARCC destination. NS2-based simulation results show that FARCC outperforms ITP and ATP to achieve, in terms of throughput and fair resource allocation in AdHoc networks under random topology.

Author Biographies

Hamideh Zare
received his B.Sc. degree on software engineering in 2007 and M.Sc. degree from the yazd university in the field of Computer Networks in 2010
Fazlollah Adibnia, yazd university
received the B.Sc. and M.Sc. degrees in the field of computer hardware engineering, and PhD degree from the Bremen University, Germany in the field of Computer Networks
Vali Derhami, yazd university
received M.Sc. and Ph.D. degrees on control engineering from Tarbiat Modares University in 1998 and 2007, respectively. Currently, he is assistant professor in ECE department in Yazd University

References

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[7] The network simulator ns-2 website, available at : http://www.isi.edu/nsnam/ns.

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http://dx.doi.org/10.1109/JSAC.2006.879365
Published
2013-06-02
How to Cite
ZARE, Hamideh; ADIBNIA, Fazlollah; DERHAMI, Vali. A Rate based Congestion Control Mechanism Using Fuzzy Controller in MANETs. INTERNATIONAL JOURNAL OF COMPUTERS COMMUNICATIONS & CONTROL, [S.l.], v. 8, n. 3, p. 486-491, june 2013. ISSN 1841-9844. Available at: <http://univagora.ro/jour/index.php/ijccc/article/view/244>. Date accessed: 23 sep. 2020. doi: https://doi.org/10.15837/ijccc.2013.3.244.

Keywords

Rate control, congestion control, fuzzy controller, channel busyness ratio