Technical Report MSC-2021-09

TR#:MSC-2021-09
Class:MSC
Title: Batched Vertex Cover Reconfiguration
Authors: Shahar Romem Peled
Supervisors: Keren Censor-Hillel
PDFMSC-2021-09.pdf
Abstract: Reconfiguration schedules, i.e., sequences that gradually transform one solution of a problem to another while always maintaining feasibility, have been extensively studied. Most research has dealt with the decision problem of whether a reconfiguration schedule exists, and the complexity of finding one. A prime example is the reconfiguration of vertex covers (sets of vertices that touches all edges in a graph). We initiate the study of \emph{batched vertex cover reconfiguration}, which allows to reconfigure multiple vertices concurrently while requiring that any adversarial reconfiguration order within a \emph{batch} maintains feasibility. The latter provides robustness, e.g., if the simultaneous reconfiguration of a batch cannot be guaranteed. The quality of a schedule is measured by the number of batches until all nodes are reconfigured, and its \emph{cost}, i.e., the maximum size of an intermediate vertex cover.

First, we design a black-box compression scheme that for any graph, takes any well-behaved sequential (= non-batched) vertex cover reconfiguration schedule and compresses it into a short batch schedule, while only incurring a $1+\varepsilon$ multiplicative increase in the cost when using $O(1/\varepsilon)$ batches; we show that this is optimal. Second, we show that a similar transformation scheme can be efficiently run in a distributed setting, where computation is done at the vertices. The distributed result is based on the new concept of a \emph{small separator decomposition} that could be of independent interest.

In addition, we show that this approach is optimal, in the sense that if a small separator decomposition does not yield a good schedule, no method will.

Both results apply to various graph classes such as chordal graphs and cacti, and provide efficient approximation schemes that have polynomial run-time in the centralized setting and take $O(\log^* n/\eps)$ rounds in the distributed setting.

Lastly, we propose greedy-style sequential and batch reconfiguration schedules and study their performance for graphs of bounded arboricity. as well as their distributed implementation.

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