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Models of Smoothing in Dynamic Networks
2020
International Symposium on Distributed Computing
Smoothed analysis is a framework suggested for mediating gaps between worst-case and average-case complexities. In a recent work, Dinitz et al. [Distributed Computing, 2018] suggested to use smoothed analysis in order to study dynamic networks. Their aim was to explain the gaps between real-world networks that function well despite being dynamic, and the strong theoretical lower bounds for arbitrary networks. To this end, they introduced a basic model of smoothing in dynamic networks, where an
doi:10.4230/lipics.disc.2020.36
dblp:conf/wdag/MeirPS20
fatcat:s3x3wkno3bgfxbhrib2u3z5a7e