2017/07/09 by Monika Henzinger, Henzinger, Monika, Dariusz Leniowski +3
Computer Science · #Data Structures and Algorithms (cs.DS) #FOS: Computer and information sciences #G.1.6 #cs.DS
paper · pdf · doi:10.48550/arxiv.1707.02577
10 pages, ESA 2017
arxiv created 2017/07/09 · arxiv updated 2017/07/11
In this paper, we study the problem of opening centers to cluster a set of clients in a metric space so as to minimize the sum of the costs of the centers and of the cluster radii, in a dynamic environment where clients arrive and depart, and the solution must be updated efficiently while remaining competitive with respect to the current optimal solution. We call this dynamic sum-of-radii clustering problem. We present a data structure that maintains a solution whose cost is within a constant factor of the cost of an optimal solution in metric spaces with bounded doubling dimension and whose worst-case update time is logarithmic in the parameters of the problem.