Development of Intelligent Load Balancing Algorithm in Application of Fuzzy-Neural Network 


Vol. 30,  No. 2, pp. 36-43, Feb.  2005


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  Abstract

This paper suggests a method to effectively apply an application model of fuzzy-neural network to the optimal load distribution algorithm, considering the complication and non-linearity of the web server environment. We use the clustering web server in the linux system and it consists of a load balancer that distributes the network loads and some of real servers that processes the load and responses to the client. The previous works considered only with the scrappy decision information such as the connections. That is, since the distribution algorithm depends on the input of the whole network throughput, it was proved inefficient in terms of performance improvement of the web server. With the proposed algorithm, it monitors the whole states of both network input and output. Then, it infers CPU and memory states of each real server and effectively distributes the requests of the clients. In this paper, the proposed model is compared with the previous method through simulations and we analysis the results to develop the optimal and intelligent load balancing model.

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  Cite this article

[IEEE Style]

G. Chu, W. Kim, J. Jung, H. Kim, "Development of Intelligent Load Balancing Algorithm in Application of Fuzzy-Neural Network," The Journal of Korean Institute of Communications and Information Sciences, vol. 30, no. 2, pp. 36-43, 2005. DOI: .

[ACM Style]

Gyo-soo Chu, Wan-yong Kim, Jae-yun Jung, and Hag-bae Kim. 2005. Development of Intelligent Load Balancing Algorithm in Application of Fuzzy-Neural Network. The Journal of Korean Institute of Communications and Information Sciences, 30, 2, (2005), 36-43. DOI: .

[KICS Style]

Gyo-soo Chu, Wan-yong Kim, Jae-yun Jung, Hag-bae Kim, "Development of Intelligent Load Balancing Algorithm in Application of Fuzzy-Neural Network," The Journal of Korean Institute of Communications and Information Sciences, vol. 30, no. 2, pp. 36-43, 2. 2005.

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pISSN : 1226 - 4717
eISSN : 2287 - 3880