Strongly Connected Components in Graph Streams

Frequently studied networks, such as social networks, are often massive, directed, and change over time. Thus studying network analysis algorithms in terms of data streaming is a practical model for understanding how companies and other organizations can process data in a useful, realistic way. One potentially interesting feature of a directed graph is strongly connected components. We design and analyze a strongly connected components algorithm, Distributed Look and Select in a recently developed data streaming model, X-Stream. We analyze the effectiveness of the algorithm and the key data features which allow it to perform best. Finally, we provide empirical results on the performance of the algorithm and how the setup can be used to derive additional properties of the network.