DocumentCode :
2691615
Title :
A multi-layered solution for supporting isp traffic demand using genetic algorithm
Author :
Kandavanam, G. ; Botvich, D. ; Balasubramaniam, S. ; Suganthan, P.N. ; Donnelly, W.
Author_Institution :
Waterford Inst. of Technol., Waterford
fYear :
2007
fDate :
25-28 Sept. 2007
Firstpage :
2032
Lastpage :
2039
Abstract :
This paper proposes a unique feedback governed multi layered architectural model to support ISP´s traffic demands with multiple quality of service(QoS) constraints. The proposed model consists of different modules each responsible for a particular set of tasks. The most challenging task involved in satisfying the demands is routing the traffic subject to multiple QoS constraints for multiple internet service providers (ISP). Routing the traffic subject to multiple constraints itself is known to be an NP-hard problem. This paper addresses the problem of finding the optimum routes to satisfy the demands of different ISPs, where different ISPs have different demands and their priority of QoS keep changing. A genetic algorithm (GA) which makes use of heuristic technique is proposed in this paper. All the optimum routes are found in one run of the program, therefore the chromosome selected encodes all the demanded routes. This paper also makes use of employing a tournament selection mechanism where the diversity of the population is preserved while the best chromosomes are carried to the next generation. The evolutionary property of GA is utilised in this paper to evolve to suit the changing demands. The performance and the evolutionary property of the proposed solution are shown with the simulation tests.
Keywords :
Internet; genetic algorithms; quality of service; telecommunication network routing; telecommunication traffic; ISP traffic demand; Internet service providers; genetic algorithm; multi-layered solution; quality of service; traffic routing; Biological cells; Feedback; Genetic algorithms; Monitoring; Quality of service; Resource management; Routing; Telecommunication traffic; Traffic control; Web and internet services;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Evolutionary Computation, 2007. CEC 2007. IEEE Congress on
Conference_Location :
Singapore
Print_ISBN :
978-1-4244-1339-3
Electronic_ISBN :
978-1-4244-1340-9
Type :
conf
DOI :
10.1109/CEC.2007.4424723
Filename :
4424723
Link To Document :
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