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MLP network for optimal MR decision in a large-scale nesting mobile networks

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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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Authors and Affiliations

  1. Dep. of Computer Information Engineering, Kunsan National University, Kunsan, Korea

    Jinkwan Lee, Sangjoon Park & Jongchan Lee

  2. Dept. of Information Communication & Home Networks, Korea Polytechnic IV College, Cheongju, Korea

    Jiyoung Song

  3. Dept. of Cultural Contents, Hankuk University of Foreign Studies, Seoul, Korea

    Hyunjoo Mun

  4. Dept. of Computing, Soongsil University, Seoul, Korea

    Youngsong Mun & Byunggi Kim

Authors
  1. Jinkwan Lee
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  2. Jiyoung Song
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  3. Sangjoon Park
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  4. Hyunjoo Mun
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  5. Jongchan Lee
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  6. Youngsong Mun
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  7. Byunggi Kim
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Corresponding author

Correspondence to Sangjoon Park.

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Lee, J., Song, J., Park, S. et al. MLP network for optimal MR decision in a large-scale nesting mobile networks. J Supercomput 56, 190–211 (2011). https://doi.org/10.1007/s11227-009-0362-x

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  • DOI: https://doi.org/10.1007/s11227-009-0362-x

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