Distributed Dynamic Graph Analytic Framework: Scalable Layered Multi-Modal Network Analysis

Dynamic Graph Analytic Framework (DYGRAF) is a domain agnostic framework from which data alignment, data association, and layered multi-modal network analysis can be performed. Past installments of DYGRAF have been able to provide analytic insight for small and medium-sized data sets, however scalability becomes problematic as the amount of collected data increases. In this work, we discuss extensions to DYGRAF that allow analysis to be performed over data of considerable size. By augmenting its current modules with distributed computing components, DYGRAF’s scalability can be extended to accommodate the effective analysis of the large amount of data being collected, as well as the massive layered multi-modal network derived.