Temporal Flows in Temporal Networks

Akrida, Eleni C.; Czyzowicz, Jurek; Gąsieniec, Leszek; Kuszner, Łukasz; Spirakis, Paul G.

Abstract

We introduce temporal flows on temporal networks [17, 19], i.e., networks the links of which exist only at certain moments of time. Such networks are ephemeral in the sense that no link exists after some time. Our flow model is new and differs from the “flows over time” model, also called “dynamic flows” in the literature. We show that the problem of finding the maximum amount of flow that can pass from a source vertex s to a sink vertex t up to a given time is solvable in Polynomial time, even when node buffers are bounded. We then examine mainly the case of unbounded node buffers. We provide a simplified static Time-Extended network ( STEG ), which is of polynomial size to the input and whose static flow rates are equivalent to the respective temporal flow of the temporal network; using STEG , we prove that the maximum temporal flow is equal to the minimum temporal s-t cut. We further show that temporal flows can always be decomposed into flows, each of which moves only through a journey, i.e., a directed path whose successive edges have strictly increasing moments of existence. We partially characterise networks with random edge availabilities that tend to eliminate the s→t temporal flow. We then consider mixed temporal networks, which have some edges with specified availabilities and some edges with random availabilities; we show that it is #P-hard to compute the tails and expectations of the maximum temporal flow (which is now a random variable) in a mixed temporal network.

Citation

Akrida, E. C., Czyzowicz, J., Gąsieniec, L., Kuszner, Ł., & Spirakis, P. G. (2017, December). Temporal Flows in Temporal Networks. Presented at 10th International Conference in Algorithms and Complexity, CIAC 2017, Athens, Greece

• Presentation Conference Type: Conference Paper (published)
• Conference Name: 10th International Conference in Algorithms and Complexity, CIAC 2017
• Online Publication Date: Apr 14, 2017
• Publication Date: 2017
• Deposit Date: Oct 25, 2021
• Publicly Available Date: Oct 26, 2021
• Print ISSN: 0302-9743
• Volume: 10236
• Pages: 43-54
• Series Title: Lecture Notes in Computer Science
• Series ISSN: 0302-9743,1611-3349
• Book Title: Algorithms and Complexity
• ISBN: 9783319575858
• DOI: https://doi.org/10.1007/978-3-319-57586-5_5
• Public URL: https://durham-repository.worktribe.com/output/1138824