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arXiv · 1811.11197

Node Diversification in Complex Networks by Decentralized Coloring

Richard Garcia-Lebron·David J. Myers·Shouhuai Xu·Jie Sun
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Abstract

We develop a decentralized coloring approach to diversify the nodes in a complex network. The key is the introduction of a local conflict index that measures the color conflicts arising at each node which can be efficiently computed using only local information. We demonstrate via both synthetic and real-world networks that the proposed approach significantly outperforms random coloring as measured by the size of the largest color-induced connected component. Interestingly, for scale-free networks further improvement of diversity can be achieved by tuning a degree-biasing weighting parameter in the local conflict index.

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Richard Garcia-Lebron, David J. Myers, Shouhuai Xu, Jie Sun. 2018-11-27. Node Diversification in Complex Networks by Decentralized Coloring. https://doi.org/10.1093/comnet%2Fcny031

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