MLP network for optimal MR decision in a large-scale nesting mobile networks |
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Authors: | Jinkwan Lee Jiyoung Song Sangjoon Park Hyunjoo Mun Jongchan Lee Youngsong Mun Byunggi Kim |
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Affiliation: | (1) Software System Lab., Department of Computer Science & Engineering, Korea University, 1, 5-ga, Anam-dong, Seongbuk-gu, Seoul, 136-701, Republic of Korea |
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Abstract: | The MR (Mobile Router) by existing top-down or bottom-up methods may not be the optimal MR if the numbers of mobile nodes
and routers are substantially increased, and the scale of the network is increased drastically. Since an inappropriate MR
decision causes handover or binding renewal to mobile nodes, determining of the optimal MR is important for efficiency. In
this paper, we propose an algorithm that decides on the optimal MR using MR QoS information, and we describe how to understand
the various structured MLP (Multi-Layered Perceptron) based on the algorithm. In conclusion, we prove the ability of the suggested
neural network for a nesting mobile network through the performance analysis of each learned MLP. |
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