Recurrent Problems in the LOCAL model
Akanksha Agrawal, John Augustine, David Peleg, Srikkanth Ramachandran

TL;DR
This paper extends the SUPPORTED model for distributed computing to include new problem types and demonstrates its effectiveness through recurrent variants of classical graph problems, achieving efficient solutions in specific graph classes.
Contribution
It broadens the SUPPORTED model's applicability to more problem types and provides new algorithms for recurrent graph problems with improved complexity bounds.
Findings
Constant time approximation for CDS on trees and planar graphs
Recurrent coloring completion with minimized new colors
Complexity dichotomy for recurrent LCL problems on paths
Abstract
The paper considers the SUPPORTED model of distributed computing introduced by Schmid and Suomela [HotSDN'13], generalizing the LOCAL and CONGEST models. In this framework, multiple instances of the same problem, differing from each other by the subnetwork to which they apply, recur over time, and need to be solved efficiently online. To do that, one may rely on an initial preprocessing phase for computing some useful information. This preprocessing phase makes it possible, in some cases, to overcome locality-based time lower bounds. A first contribution of the current paper is expanding the spectrum of problem types to which the SUPPORTED model applies. In addition to subnetwork-defined recurrent problems, we introduce also recurrent problems of two additional types: (i) instances defined by partial client sets, and (ii) instances defined by partially fixed outputs. Our second…
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