Abstract
One of the most important issues in multicast is how to achieve a balanced traffic load within a communications network. This paper formulates a load balancing optimization problem in the context of multicast with network coding and proposes a modified population based incremental learning (PBIL) algorithm for tackling it. A novel probability vector update scheme is developed to enhance the global exploration of the stochastic search by introducing extra flexibility when guiding the search towards promising areas in the search space. Experimental results demonstrate that the proposed PBIL outperforms a number of the state-of-the-art evolutionary algorithms in terms of the quality of the best solution obtained.
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Acknowledgements
This research was supported in part by NSFC (No.61401374), the Fundamental Research Funds for the Central Universities (No. 2682014RC23), the Project-sponsored by SRF for ROCS, SEM, P. R. China and University of Nottingham, UK.
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Xing, H., Xu, Y., Qu, R., Xu, L. (2016). A PBIL for Load Balancing in Network Coding Based Multicasting. In: Gervasi, O., et al. Computational Science and Its Applications – ICCSA 2016. ICCSA 2016. Lecture Notes in Computer Science(), vol 9787. Springer, Cham. https://doi.org/10.1007/978-3-319-42108-7_3
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DOI: https://doi.org/10.1007/978-3-319-42108-7_3
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