A Local Tuning Scheme of RED using Genetic Algorithm for Efficient Network Management in Muti-Core CPU Environment

Ja-Young Song; Byeong-Seog Choe

A Local Tuning Scheme of RED using Genetic Algorithm for Efficient Network Management in Muti-Core CPU Environment

Ja-Young Song, Byeong-Seog Choe, Journal of Internet Computing and Services, Vol. 11, No. 1, pp. 1-14, Feb. 2010
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Keywords: Network Management, Active Queue Management, Congestion Control

Abstract

It is not easy to set RED(Random Early Detection) parameter according to environment in managing Network Device. Especially, it is more difficult to set parameter in the case of maintaining the constant service rate according to the change of environment. In this paper, we hypothesize the router that has Multi-core CPU in output queue and propose AI RED(Artificial Intelligence RED), which directly induces Genetic Algorithm of Artificial Intelligence in the output queue that is appropriate to the optimization of parameter according to RED environment, which is automatically adaptive to workload. As a result, AI RED Is simpler and finer than FuRED(Fuzzy-Logic-based RED), and RED parameter that AI RED searches through simulations is more adaptive to environment than standard RED parameter, providing the effective service. Consequently, the automation of management of RED parameter can provide a manager with the enhancement of efficiency in Network management.

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Cite this article

[APA Style]

Song, J. & Choe, B. (2010). A Local Tuning Scheme of RED using Genetic Algorithm for Efficient Network Management in Muti-Core CPU Environment. Journal of Internet Computing and Services, 11(1), 1-14.

[IEEE Style]

J. Song and B. Choe, "A Local Tuning Scheme of RED using Genetic Algorithm for Efficient Network Management in Muti-Core CPU Environment," Journal of Internet Computing and Services, vol. 11, no. 1, pp. 1-14, 2010.

[ACM Style]

Ja-Young Song and Byeong-Seog Choe. 2010. A Local Tuning Scheme of RED using Genetic Algorithm for Efficient Network Management in Muti-Core CPU Environment. Journal of Internet Computing and Services, 11, 1, (2010), 1-14.