This paper presents an algorithm for estimating the weight of a maximum weighted matching by augmenting any estimation routine for the size of an unweighted matching. The algorithm is implementable in any streaming model including dynamic graph streams. We also give the first constant estimation for the maximum matching size in a dynamic graph stream for planar graphs (or any graph with bounded arboricity) using Õn4/5) space which also extends to weighted matching. Using previous results by Kapralov, Khanna, and Sudan (2014) we obtain a polylog(n) approximation for general graphs using polylog(n) space in random order streams, respectively. In addition, we give a space lower bound of Ω(n1−ε) for any randomized algorithm estimating the size of a maximum matching up to a 1+O(ε) factor for adversarial streams.
CITATION STYLE
Bury, M., & Schwiegelshohn, C. (2015). Sublinear estimation of weighted matchings in dynamic data streams. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 9294, pp. 263–274). Springer Verlag. https://doi.org/10.1007/978-3-662-48350-3_23
Mendeley helps you to discover research relevant for your work.