An application of genetic fuzzy system to improve the random exponential marking algorithm in active queue management

Author

Phuong Huy Nguyen ; Ba Dung Le

Author_Institution

Thai Nguyen Univ. of Technol., Thai Nguyen, Vietnam

fYear

2012

fDate

16-18 Oct. 2012

Firstpage

1552

Lastpage

1556

Abstract

Active Queue Management algorithms (AQM) are setup in routers on telecommunication networks in order to provide a mechanism to mark or discard packets in an appropriate way so as not to cause congestion on network and maintain the best quality of services with different traffic flows. Previous methods of AQM are designed with fixed parameters so It should not really online adapt to the network dynamic. To overcome this drawback, this paper proposed a new algorithm to improve Random Exponential Marking (REM) by combining fuzzy system and genetic algorithm. This new method allows automatic adjustment of parameters with the network dynamic. Results are verified through software simulation on NS2.

Keywords

fuzzy systems; genetic algorithms; quality of service; queueing theory; random processes; telecommunication congestion control; telecommunication network management; telecommunication network routing; telecommunication traffic; AQM algorithm; NS2 software simulation; REM algorithm; active queue management algorithm; genetic algorithm; genetic fuzzy system; quality of services; random exponential marking algorithm; telecommunication network routing; traffic flow; Active Queue Managemen; Genetic Fuzzy System; Random Exponential Marking;

fLanguage

English

Publisher

ieee

Conference_Titel

Biomedical Engineering and Informatics (BMEI), 2012 5th International Conference on

Conference_Location

Chongqing

Print_ISBN

978-1-4673-1183-0

Type

conf

DOI

10.1109/BMEI.2012.6513179

Filename

6513179