Brief Announcement: Using Read-K Inequalities To Analyze A Distributed Mis Algorithm

Until recently, the fastest distributed MIS algorithm, even for simple graphs, e.g., unoriented trees has been the simple randomized algorithm discovered the 80s. This algorithm (commonly called Luby's algorithm) computes an MIS in O(logn) rounds (with high probability). This situation changed when Lenzen and Wattenhofer (PODC 2011) presented a randomized O(root log n . log log n)-round MIS algorithm for unoriented trees. This algorithm was improved by Barenboim et al. (FOCS 2012), resulting in an O(root log n . log log n)-round MIS algorithm.The analyses of these tree MIS algorithms depends on "near independence" of probabilistic events, a feature of the tree structure of the network. In their paper, Lenzen and Wattenhofer hope that their algorithm and analysis could be extended to graphs with bounded arboricity. We show how to do this. By using a new tail inequality for read-k families of random variables due to Gavinsky et al. (Random Struct Algorithms, 2015), we show how to deal with dependencies induced by the recent tree MIS algorithms when they are executed on bounded arboricity graphs. Specifically, we analyze a version of the tree MIS algorithm of Barenboim et al. and show that it runs in O(poly(alpha) root log n log log n) rounds in the CONGEST model for graphs with arboricity alpha.