Journal of Communications and Networks

The Korean Institute of Commucations and Information Sciences (한국통신학회)
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Fuzzy Logic Based Neural Network Models for Load Balancing in Wireless Networks

  • Wang, Yao-Tien (Department of Information Management, Kainan University) ;
  • Hung, Kuo-Ming (Department of Information Management, Kainan University)
  • Published : 2008.03.31
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Abstract

In this paper, adaptive channel borrowing approach fuzzy neural networks for load balancing (ACB-FNN) is presented to maximized the number of served calls and the depending on asymmetries traffic load problem. In a wireless network, the call's arrival rate, the call duration and the communication overhead between the base station and the mobile switch center are vague and uncertain. A new load balancing algorithm with cell involved negotiation is also presented in this paper. The ACB-FNN exhibits better learning abilities, optimization abilities, robustness, and fault-tolerant capability thus yielding better performance compared with other algorithms. It aims to efficiently satisfy their diverse quality-of-service (QoS) requirements. The results show that our algorithm has lower blocking rate, lower dropping rate, less update overhead, and shorter channel acquisition delay than previous methods.

Keywords

References

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