Organizer: CROSSING / GRK Privacy & Trust / CRISP
Large graphs arise naturally in many real world applications. The actual performance of simple RAM model algorithms for traversing these graphs (stored in external memory) deviates significantly from their linear or near-linear predicted performance because of the large number of I/Os they incur. In order to alleviate the I/O bottleneck, many external memory graph traversal algorithms have been designed with provable worst-case guarantees.
In the talk I highlight some techniques used in the design and engineering of such algorithms and survey the state-of-the-art in I/O-efficient graph traversal algorithms. I will also report on recent work concerning the generation of massive scale free networks under resource constraints.