Abstract
The best attachment consists in finding a good strategy that allows a node inside a network to achieve a high rank. This is an open issue due to its intrinsic computational complexity and to the giant dimension of the involved networks. The ranking of a node has an important impact both in economics and structural term e.g., a higher rank could leverage the number of contacts or the trusting of the node. This paper presents a heuristics aiming at finding a good solution whose complexity is \(N\log {N}\). The results show that better rank improvement comes by acquiring long distance in-links whilst human intuition would suggest to select neighbours. The paper discusses the algorithm and simulation on random and scale-free networks.
Keywords
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Carchiolo, V., Grassia, M., Longheu, A., Malgeri, M., Mangioni, G. (2018). Climbing Ranking Position via Long-Distance Backlinks. In: Xiang, Y., Sun, J., Fortino, G., Guerrieri, A., Jung, J. (eds) Internet and Distributed Computing Systems. IDCS 2018. Lecture Notes in Computer Science(), vol 11226. Springer, Cham. https://doi.org/10.1007/978-3-030-02738-4_9
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