Worst-Case Efficient Dynamic Geometric Independent Set
Jean Cardinal, John Iacono, Grigorios Koumoutsos

TL;DR
This paper introduces a new data structure for maintaining an approximate maximum independent set of geometric objects like disks and polygons in dynamic settings, achieving sublinear worst-case update times.
Contribution
It presents the first dynamic algorithms with worst-case update bounds for geometric independent sets, using a novel deamortization scheme applicable to fat objects.
Findings
Achieves sublinear worst-case update time for dynamic independent sets.
Introduces a generic deamortization scheme for geometric objects.
Proves lower bounds showing limitations for certain classes of objects.
Abstract
We consider the problem of maintaining an approximate maximum independent set of geometric objects under insertions and deletions. We present data structures that maintain a constant-factor approximate maximum independent set for broad classes of fat objects in dimensions, where is assumed to be a constant, in sublinear \textit{worst-case} update time. This gives the first results for dynamic independent set in a wide variety of geometric settings, such as disks, fat polygons, and their high-dimensional equivalents. Our result is obtained via a two-level approach. First, we develop a dynamic data structure which stores all objects and provides an approximate independent set when queried, with output-sensitive running time. We show that via standard methods such a structure can be used to obtain a dynamic algorithm with \textit{amortized} update time bounds. Then, to obtain…
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