An intelligent routing and CAC framework for large-scale networks based on cooperative agents

The routing algorithms can be classified into source, distributed and hierarchical routing. Source routing algorithms are conceptually simple, but they suffer from scalability problem. Distributed routing algorithms are more scalable, but loops may occur, which make the routing to fail. Hierarchical routing has been used to cope with the scalability problems of source routing in large internetworks. The hierarchical routing retains many advantages of source routing. It also has some advantages of distributed routing, because the routing computation is shared by many nodes. The traffic control methods for telecommunication networks must be adaptive, flexible, and intelligent. Use of intelligent algorithms based on fuzzy logic, genetic algorithms and neural networks can prove to be efficient for traffic control in telecommunication networks. In this paper, we propose an intelligent routing and Call Admission Control framework, which is based on cooperative agents. The proposed routing algorithm is a combination of source and distributed routing. It uses source routing inside a domain and hop-by-hop routing for inter-domain. The proposed framework is able to avoid flooding and routing loops, reduce the search space, and can be easily scaled-up to cope with large-scale networks. Performance evaluation via simulations shows that the proposed Fuzzy Admission Control and Intra Domain algorithm have better performance than the conventional methods.

[1]  Erick Cantú-Paz Designing Efficient and Accurate Parallel Genetic Algorithms , 1999 .

[2]  Pawel Gburzynski,et al.  Routing in multihop packet switching networks: Gb/s challenge , 1995, IEEE Netw..

[3]  Harry G. Perros,et al.  Call admission control schemes: a review , 1996, IEEE Commun. Mag..

[4]  Chung-Ju Chang,et al.  Design of a fuzzy traffic controller for ATM networks , 1996, TNET.

[5]  Nadia Boukhatem,et al.  Cooperative congestion control schemes in ATM networks , 1996 .

[6]  Christos Douligeris,et al.  Fuzzy multiobjective routing model in B-ISDN , 1998, Comput. Commun..

[7]  Didier Dubois,et al.  Readings in Fuzzy Sets for Intelligent Systems , 1993 .

[8]  H. T. Mouftah,et al.  Dynamic routing for multimedia traffic over ATM networks , 1995, Proceedings IEEE Symposium on Computers and Communications.

[9]  P. Chemouil,et al.  Application of fuzzy control to adaptive traffic routing in telephone network , 1994 .

[10]  Leonard Barolli,et al.  An intelligent policing-routing mechanism based on fuzzy logic and genetic algorithms , 1998, Proceedings 1998 International Conference on Parallel and Distributed Systems (Cat. No.98TB100250).

[11]  Frank Yeong-Sung Lin,et al.  A real-time distributed routing and admission control algorithm for ATM networks , 1993, IEEE INFOCOM '93 The Conference on Computer Communications, Proceedings.

[12]  David E. Goldberg,et al.  Designing efficient and accurate parallel genetic algorithms (parallel algorithms) , 1999 .

[13]  Andrew S. Tanenbaum,et al.  Computer Networks , 1981 .

[14]  Christos Douligeris,et al.  Neuro-fuzzy control in ATM networks , 1997, IEEE Commun. Mag..

[15]  David E. Goldberg,et al.  Genetic Algorithms in Search Optimization and Machine Learning , 1988 .

[16]  Robert Cole,et al.  Computer Communications , 1982, Springer New York.

[17]  Piet Demeester,et al.  Pan-European optical networking using wavelength division multiplexing , 1997, IEEE Commun. Mag..

[18]  Pierre A. Humblet,et al.  Routing subject to quality of service constraints in integrated communication networks , 1995, IEEE Netw..

[19]  Jon Crowcroft,et al.  Quality-of-Service Routing for Supporting Multimedia Applications , 1996, IEEE J. Sel. Areas Commun..

[20]  Erol Gelenbe,et al.  Guest editorial: intelligent techniques in high speed networks , 2000, IEEE J. Sel. Areas Commun..

[21]  Hamid Ahmadi,et al.  Equivalent Capacity and Its Application to Bandwidth Allocation in High-Speed Networks , 1991, IEEE J. Sel. Areas Commun..