Nearly Optimal Dynamic Set Cover: Breaking the Quadratic-in-$f$ Time Barrier
The dynamic set cover problem has been subject to extensive research since the pioneering works of [Bhattacharya et al, 2015] and [Gupta et al, 2017]. The input is a set system $(U, S)$ on a fixed collection $S$ of sets and a dynamic universe of elements, where each element appears in a most $f$ set...
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Zusammenfassung: | The dynamic set cover problem has been subject to extensive research since
the pioneering works of [Bhattacharya et al, 2015] and [Gupta et al, 2017]. The
input is a set system $(U, S)$ on a fixed collection $S$ of sets and a dynamic
universe of elements, where each element appears in a most $f$ sets and the
cost of each set lies in the range $[1/C, 1]$, and the goal is to efficiently
maintain an approximately-minimum set cover under insertions and deletions of
elements.
Most previous work considers the low-frequency regime, namely $f = O(\log
n)$, and this line of work has culminated with a deterministic
$(1+\epsilon)f$-approximation algorithm with amortized update time
$O(\frac{f^2}{\epsilon^3} + \frac{f}{\epsilon^2}\log C)$ [Bhattacharya et al,
2021]. In the high-frequency regime of $f = \Omega(\log n)$, an $O(\log
n)$-approximation algorithm with amortized update time $O(f\log n)$ was given
by [Gupta et al, 2017].
Interestingly, at the intersection of the two regimes, i.e., $f = \Theta(\log
n)$, the state-of-the-art results coincide: approximation $\Theta(f) =
\Theta(\log n)$ with amortized update time $O(f^2) = O(f \log n) = O(\log^2
n)$. Up to this date, no previous work achieved update time of $o(f^2)$.
In this paper we break the $\Omega(f^2)$ update time barrier via the
following results: (1) $(1+\epsilon)f$-approximation can be maintained in
$O\left(\frac{f}{\epsilon^3}\log^*f + \frac{f}{\epsilon^3}\log C\right) =
O_{\epsilon,C}(f \log^* f)$ expected amortized update time; our algorithm works
against an adaptive adversary. (2) $(1+\epsilon)f$-approximation can be
maintained deterministically in $O\left(\frac{1}{\epsilon}f\log f +
\frac{f}{\epsilon^3} + \frac{f\log C}{\epsilon^2}\right) = O_{\epsilon,C}(f
\log f)$ amortized update time. |
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DOI: | 10.48550/arxiv.2308.00793 |