%0 Journal Article
%T Improved approximation guarantees for weighted matching in the semi-streaming model
%A Leah Epstein
%A Asaf Levin
%A Julian Mestre
%A Danny Segev
%J Computer Science
%D 2009
%I arXiv
%R 10.1137/100801901
%X We study the maximum weight matching problem in the semi-streaming model, and improve on the currently best one-pass algorithm due to Zelke (Proc. of STACS2008, pages 669-680) by devising a deterministic approach whose performance guarantee is 4.91+epsilon. In addition, we study preemptive online algorithms, a sub-class of one-pass algorithms where we are only allowed to maintain a feasible matching in memory at any point in time. All known results prior to Zelke's belong to this sub-class. We provide a lower bound of 4.967 on the competitive ratio of any such deterministic algorithm, and hence show that future improvements will have to store in memory a set of edges which is not necessarily a feasible matching.
%U http://arxiv.org/abs/0907.0305v1