Abstract
The interest in dynamic processes on networks is steadily rising in recent years. In this paper, we consider the \((\alpha ,\beta )\)-Thresholded Network Dynamics (\((\alpha ,\beta )\)-Dynamics), where \(\alpha \le \beta \), in which only structural dynamics (dynamics of the network) are allowed, guided by local thresholding rules executed by each node. In particular, in each discrete round t, each pair of nodes u and v that are allowed to communicate by the scheduler, computes a value \(\mathcal {E}(u,v)\) (the potential of the pair) as a function of the local structure of the network at round t around the two nodes. If \(\mathcal {E}(u,v) < \alpha \) then the link (if it exists) between u and v is removed; if \(\alpha \le \mathcal {E}(u,v) < \beta \) then an existing link among u and v is maintained; if \(\beta \le \mathcal {E}(u,v)\) then a link between u and v is established if not already present.
The microscopic structure of \((\alpha ,\beta )\)-Dynamics appears to be simple, so that we are able to rigorously argue about it, but still flexible, so that we are able to design meaningful microscopic local rules that give rise to interesting macroscopic behaviors. Our goals are the following: a) to investigate the properties of the \((\alpha ,\beta )\)-Thresholded Network Dynamics and b) to show that \((\alpha ,\beta )\)-Dynamics is expressive enough to solve complex problems on networks.
Our contribution in these directions is twofold. We rigorously exhibit the claim about the expressiveness of \((\alpha ,\beta )\)-Dynamics, both by designing a simple protocol that provably computes the k-core of the network as well as by showing that \((\alpha ,\beta )\)-Dynamics are in fact Turing-Complete. Second and most important, we construct general tools for proving stabilization that work for a subclass of \((\alpha ,\beta )\)-Dynamics and prove speed of convergence in a restricted setting.
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Notes
- 1.
Therefore, we only use identifiers of nodes for analysis purposes.
- 2.
The permanence of enmity is in fact not exactly compatible with structural balance theory on networks.
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Funding
Evangelos Kipouridis: Received funding from the European Unions Horizon 2020 research and innovation program under the Marie Sklodowska-Curie grant agreement No 801199. Evangelos Kipouridis is also supported by Thorups Investigator Grant 16582, Basic Algorithms Research Copenhagen (BARC), from the VILLUM Foundation.
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Kipouridis, E., Spirakis, P.G., Tsichlas, K. (2021). Threshold-Based Network Structural Dynamics. In: Jurdziński, T., Schmid, S. (eds) Structural Information and Communication Complexity. SIROCCO 2021. Lecture Notes in Computer Science(), vol 12810. Springer, Cham. https://doi.org/10.1007/978-3-030-79527-6_8
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