Keywords: Clustering, Facility Location, Dynamic Algorithms, Consistent, Recourse, Approximation
TL;DR: We provide the first algorithm for the dynamic facility location problem that at the same time maintains a constant approximation, uses polylogarithmic time per update, and incurs polylogarithmic recourse per update.
Abstract: We consider the classic facility location problem in fully dynamic data streams, where elements can be both inserted and deleted. In this problem, one is interested in maintaining a stable and high quality solution throughout the data stream while using only little time per update (insertion or deletion). We study the problem and provide the first algorithm that at the same time maintains a constant approximation and incurs polylogarithmic amortized recourse per update. We complement our theoretical results with an experimental analysis showing the practical efficiency of our method.
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