
handle: 11573/44659
We give a distributed randomized algorithm to edge colour a network. Let G be a graph<br />with n nodes and maximum degree Delta. Here we prove:<br /> If Delta = Omega(log^(1+delta) n) for some delta > 0 and lambda > 0 is fixed, the algorithm almost always<br />colours G with (1 + lambda)Delta colours in time O(log n).<br /> If s > 0 is fixed, there exists a positive constant k such that if Delta = omega(log^k n), the algorithm almost always colours G with Delta + Delta / log^s n = (1+o(1))Delta colours in time<br />O(logn + log^s n log log n).<br />By "almost always" we mean that the algorithm may fail, but the failure probability can be<br />made arbitrarily close to 0.<br />The algorithm is based on the nibble method, a probabilistic strategy introduced by<br />Vojtech R¨odl. The analysis makes use of a powerful large deviation inequality for functions<br />of independent random variables.
distributed algorithms, Large deviation inequalities, randomized algorithms, large deviation inequalities, Randomized algorithms, Edge colouring, Theoretical Computer Science, edge colouring, Graph theory (including graph drawing) in computer science, Distributed algorithms, Parallel algorithms in computer science, Computer Science(all)
distributed algorithms, Large deviation inequalities, randomized algorithms, large deviation inequalities, Randomized algorithms, Edge colouring, Theoretical Computer Science, edge colouring, Graph theory (including graph drawing) in computer science, Distributed algorithms, Parallel algorithms in computer science, Computer Science(all)
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