19,916 research outputs found
Recent Advances in Graph Partitioning
We survey recent trends in practical algorithms for balanced graph
partitioning together with applications and future research directions
Learning-Based Constraint Satisfaction With Sensing Restrictions
In this paper we consider graph-coloring problems, an important subset of
general constraint satisfaction problems that arise in wireless resource
allocation. We constructively establish the existence of fully decentralized
learning-based algorithms that are able to find a proper coloring even in the
presence of strong sensing restrictions, in particular sensing asymmetry of the
type encountered when hidden terminals are present. Our main analytic
contribution is to establish sufficient conditions on the sensing behaviour to
ensure that the solvers find satisfying assignments with probability one. These
conditions take the form of connectivity requirements on the induced sensing
graph. These requirements are mild, and we demonstrate that they are commonly
satisfied in wireless allocation tasks. We argue that our results are of
considerable practical importance in view of the prevalence of both
communication and sensing restrictions in wireless resource allocation
problems. The class of algorithms analysed here requires no message-passing
whatsoever between wireless devices, and we show that they continue to perform
well even when devices are only able to carry out constrained sensing of the
surrounding radio environment
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