Discrete Integral and Discrete Derivative on Graphs and Switch Problem of Trees

Author:

Khalifeh M. H.1ORCID,Esfahanian Abdol-Hossein1

Affiliation:

1. Department of Computer Science and Engineering, Michigan State University, East Lansing, MI 48824, USA

Abstract

For a vertex and edge weighted (VEW) graph G with a vertex weight function fG let Wα,β(G)=∑{u,v}⊆V(G)[αfG(u)×fG(v)+β(fG(u)+fG(v))]dG(u,v) where, α,β∈ℝ and dG(u,v) denotes the distance, the minimum sum of edge weights across all the paths connecting u,v∈V(G). Assume T is a VEW tree, and e∈ E(T) fails. If we reconnect the two components of T−e with new edge ϵ≠e such that, Wα,β(Tϵ\e=T−e+ϵ) is minimum, then ϵ is called a best switch (BS) of e w.r.t. Wα,β. We define three notions: convexity, discrete derivative, and discrete integral for the VEW graphs. As an application of the notions, we solve some BS problems for positively VEW trees. For example, assume T is an n-vertex VEW tree. Then, for the inputs e∈ E(T) and w,α,β ∈ℝ+, we return ϵ, Tϵ\e, and Wα,β(Tϵ\e) with the worst average time of O(logn) and the best time of O(1) where ϵ is a BS of e w.r.t. Wα,β and the weight of ϵ is w.

Funder

NSF Program on Fairness in AI in collaboration with Amazon

Publisher

MDPI AG

Subject

General Mathematics,Engineering (miscellaneous),Computer Science (miscellaneous)

Reference31 articles.

1. State space partition algorithms for stochastic systems with applications to minimum spanning trees;Alexopoulos;Networks,2000

2. Aziz, F., Gul, H., Uddin, I., and Gkoutos, G.V. (2020). Path-based extensions of local link prediction methods for complex networks. Sci. Rep., 10.

3. Hunting for vital nodes in complex networks using local information;Dong;Sci. Rep.,2021

4. Hamilton, W.L., Ying, R., and Leskovec, J. (2017, January 4–9). Inductive representation learning on large graphs. Proceedings of the 31st International Conference on Neural Information Processing Systems, NIPS’17, Red Hook, NY, USA.

5. Progresses and challenges in link prediction;Zhou;iScience,2021

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