Analyze Infrastructure Networks With Dynamic Betweenness Centrality

Ante Pusic's blog post explores the impact of disruptions in the global submarine internet cable network using dynamic betweenness centrality, particularly when connections are lost due to unforeseen events like shark attacks. By employing Memgraph's graph analytics capabilities, including online graph algorithms like Node2Vec and PageRank, the analysis focuses on updating previous outputs rather than recalculating everything, thus allowing a rapid response to network changes. By utilizing Docker, GQLAlchemy, and Jupyter Notebook, the blog details setting up Memgraph and analyzing the submarine cable network graph, with nodes representing landing points and edges representing cables. The iCentral algorithm is discussed as a new advancement, enabling efficient recalculations of betweenness centrality scores by focusing only on affected areas of the graph, thereby improving performance and scalability. The post illustrates this with an example where a cable cut between Tuas, Singapore, and Jeddah, Saudi Arabia, prompts updates in centrality scores, highlighting the dynamic nature of internet traffic flow. The blog concludes by emphasizing the importance of online algorithms for scaling graph analytics and invites community engagement through Memgraph's open-source projects and Discord channel.