Full Text:   <4274>

CLC number: TN915.11

On-line Access: 

Received: 2008-02-20

Revision Accepted: 2008-06-10

Crosschecked: 2008-11-10

Cited: 2

Clicked: 5980

Citations:  Bibtex RefMan EndNote GB/T7714

-   Go to

Article info.
1. Reference List
Open peer comments

Journal of Zhejiang University SCIENCE A 2008 Vol.9 No.12 P.1666-1675


AFAR: adaptive fuzzy ant-based routing for communication networks

Author(s):  Seyed Javad MIRABEDINI, Mohammad TESHNEHLAB, M. H. SHENASA, Ali MOVAGHAR, Amir Masoud RAHMANI

Affiliation(s):  Engineering Department, Science and Research Branch, Islamic Azad University, Tehran, Iran; more

Corresponding email(s):   jvd2205@yahoo.com

Key Words:  Adaptive fuzzy routing algorithm, Swarm intelligence, Routing table, Communication network, Packet delay, Throughput

Seyed Javad MIRABEDINI, Mohammad TESHNEHLAB, M. H. SHENASA, Ali MOVAGHAR, Amir Masoud RAHMANI. AFAR: adaptive fuzzy ant-based routing for communication networks[J]. Journal of Zhejiang University Science A, 2008, 9(12): 1666-1675.

@article{title="AFAR: adaptive fuzzy ant-based routing for communication networks",
author="Seyed Javad MIRABEDINI, Mohammad TESHNEHLAB, M. H. SHENASA, Ali MOVAGHAR, Amir Masoud RAHMANI",
journal="Journal of Zhejiang University Science A",
publisher="Zhejiang University Press & Springer",

%0 Journal Article
%T AFAR: adaptive fuzzy ant-based routing for communication networks
%A Amir Masoud RAHMANI
%J Journal of Zhejiang University SCIENCE A
%V 9
%N 12
%P 1666-1675
%@ 1673-565X
%D 2008
%I Zhejiang University Press & Springer
%DOI 10.1631/jzus.A0820118

T1 - AFAR: adaptive fuzzy ant-based routing for communication networks
A1 - Seyed Javad MIRABEDINI
A1 - Mohammad TESHNEHLAB
A1 - Amir Masoud RAHMANI
J0 - Journal of Zhejiang University Science A
VL - 9
IS - 12
SP - 1666
EP - 1675
%@ 1673-565X
Y1 - 2008
PB - Zhejiang University Press & Springer
ER -
DOI - 10.1631/jzus.A0820118

We propose a novel approach called adaptive fuzzy ant-based routing (AFAR), where a group of intelligent agents (or ants) builds paths between a pair of nodes, exploring the network concurrently and exchanging obtained information to update the routing tables. Routing decisions can be made by the fuzzy logic technique based on local information about the current network state and the knowledge constructed by a previous set of behaviors of other agents. The fuzzy logic technique allows multiple constraints such as path delay and path utilization to be considered in a simple and intuitive way. Simulation tests show that AFAR outperforms OSPF, AntNet and ASR, three of the currently most important state-of-the-art algorithms, in terms of end-to-end delay, packet delivery, and packet drop ratio. AFAR is a promising alternative for routing of data in next generation networks.

Darkslateblue:Affiliate; Royal Blue:Author; Turquoise:Article


[1] Akon, M.M., Goswami, D., Jyoti, S.A., 2004. Routing in Telecommunication Network with Controlled Ant Population. Proc. 1st IEEE Consumer Communications and Networking Conf., p.665-667.

[2] Barabási, A., Bonabeau, E., 2003. Scale-free networks. Sci. Amer., 288(5):50-59.

[3] Barán, B., Sosa, R., 2001. AntNet routing algorithm for data networks based on mobile agents. Inteligencia Artificial, Revista Iberoamericana de Inteligencia Artificial, 12:75-84.

[4] Birattari, M., di Caro, G.A., Dorigo, M., 2002. Toward the formal foundation of ant programming. LNCS, 2463:188-201.

[5] Cheng, X., Hou, Y.B., 2003. A Study of Genetic Ant Routing Algorithm. Proc. Int. Conf. on Machine Learning and Cybernetics, p.2041-2045.

[6] di Caro, G.A., Vasilakos, T., 2000. Ant-SELA: Ant-agents and Stochastic Automata Learn Adaptive Routing Tables for QoS Routing in ATM Networks. Ant Colonies to Artificial Ants: Second Int. Workshop on Ant Colony Optimization, Brussels, Belgium, p.101-104.

[7] Dorigo, M., di Caro, G., 1998. AntNet: distributed stigmergetic control for communications networks. J. Artif. Intell. Res., 9:317-365.

[8] Dorigo, M., di Caro, G., 1999. Ant Colony Optimization: A New Meta-heuristic. Proc. Congresson Evolutionary Computation, p.1470-1477.

[9] Ducatelle, F., di Caro, G., Gambardella, L.M., 2006. An analysis of the different components of the AntHocNet routing algorithm. LNCS, 4150:37-48.

[10] Katangur, A.K., Akkaladevi, S., Yi, P., Fraser, M.D., 2004. Applying Ant Colony Optimization to Routing in Optical Multistage Interconnection Networks with Limited Crosstalk. Proc. 18th Int. Parallel and Distributed Processing Symp., p.163-170.

[11] Lü, Y., Zhao, G.Z., Su, F.J., Li, X.R., 2004. Adaptive swarm-based routing in communication networks. J. Zhejiang Univ. Sci., 5(7):867-872.

[12] Mirabedini, S.J., Teshnehlab, M., 2004. AntNeuroFuzzy: Optimal Solution for Traveling Salesman Problem Using Ant Colony and Neuro-fuzzy Systems. Proc. ICTIT Int. Conf., p.305-312.

[13] Mirabedini, S.J., Teshnehlab, M., 2007a. Performance evaluation of fuzzy ant based routing method in connectionless networks. LNCS, 4488:960-965.

[14] Mirabedini, S.J., Teshnehlab, M., 2007b. FuzzyAntNet: a novel multi-agent routing algorithm for communications networks. GESJ: Comput. Sci. Telecommun., 12(1):45-49.

[15] Mirabedini, S.J., Teshnehlab, M., Rahmani, A.M., 2007. FLAR: An Adaptive Fuzzy Routing Algorithm for Communications Networks Using Mobile Ants. Proc. Int. Conf. on Convergence Information Technology, p.1308-1315.

[16] Sarif, B.A.B., Abd-El-Barr, M., Sait, S.M., Al-Saiari, U., 2004. Fuzzified Ant Colony Optimization Algorithm for Efficient Combinatorial Circuit Synthesis. Proc. IEEE Congress on Evolutionary Computation, p.1317-1324.

[17] Sim, K.M., Sun, W.H., 2002. Multiple Ant-Colony Optimization for Network Routing. Proc. 1st Int. Symp. on Cyber Worlds, p.277-281.

[18] Sim, K.M., Sun, W.H., 2003. Ant colony optimization for routing and load-balancing: survey and new directions. IEEE Trans. on Syst. Man Cybern., Part A, 33(5):560-572.

[19] Singh, G., Das, S., Gosavi, S., Pujar, S., 2008. Ant Colony Algorithms for Steiner Trees: An Application to Routingin Sensor Networks. In: Sugumaran, V. (Ed.), Intelligent Information Technologies: Concepts, Methodologies, Tools and Applications. Idea Group Publishing, USA, p.1551-1575.

[20] Tannenbaum, A.S., 2003. Computer Networks (4th Ed.). Prentice Hall, New Jersey.

[21] Zhang, R.T., Phillis, Y., 2001. Admission control and scheduling in simple series parallel networks using fuzzy logic. IEEE Trans. on Fuzzy Syst., 9(2):307-314.

[22] Zhang, S., Liu, Z., 2001. A QoS Routing Algorithm Based on Ant Algorithm. Proc. IEEE Int. Conf. on Communications, 5:1581-1585.

Open peer comments: Debate/Discuss/Question/Opinion



2010-02-20 04:12:09

Very excellent paper

Please provide your name, email address and a comment

Journal of Zhejiang University-SCIENCE, 38 Zheda Road, Hangzhou 310027, China
Tel: +86-571-87952783; E-mail: cjzhang@zju.edu.cn
Copyright © 2000 - 2024 Journal of Zhejiang University-SCIENCE