Optimizing the topology of an end-to-end ATM environment

Author

Lee, C.S. ; Tan, T.K.

Author_Institution

Sch. of Biophysical Sci. & Electr. Eng., Swinburne Univ. of Technol., Hawthorn, Vic., Australia

fYear

1995

fDate

3-7 Jul 1995

Firstpage

86

Lastpage

90

Abstract

Finding an optimal topology for a wide area network is a complex task which involves solving some form of simultaneous constrained optimization problem. Heuristic approaches have been widely used for solving this class of problems. This paper discusses the formulation of this class of problems as optimizing the topology of an artificial neural network and the use of genetic algorithms as heuristics inputs to the artificial neural networks for an end-to-end ATM environment

Keywords

asynchronous transfer mode; genetic algorithms; heuristic programming; neural nets; wide area networks; artificial neural network; end-to-end ATM environment; genetic algorithms; heuristic approaches; simultaneous constrained optimization problem; topology optimisation; wide area network; Asynchronous transfer mode; Broadcasting; Ethernet networks; LAN emulation; Local area networks; Network servers; Network topology; Neural networks; Switches; Wide area networks;

fLanguage

English

Publisher

ieee

Conference_Titel

Networks, 1995. Theme: Electrotechnology 2000: Communications and Networks. [in conjunction with the] International Conference on Information Engineering., Proceedings of IEEE Singapore International

Print_ISBN

0-7803-2579-6

Type

conf

DOI

10.1109/SICON.1995.525997

Filename

525997