The researches of temporal graph have been conducted in interdisciplinary fields and applied to various kinds of networks; online social network, cell biology network, neural network, ecological network, etc. However, processing and understanding the networks would be complicated for application developers due to their high velocity and volume. Also, the heterogeneity of the networks incurs their unified usage. Therefore, we propose the online graph processing middleware for temporal networks, namely Hairspring. The middleware is based on the temporal property graph, which we leverage the property graph model, Blueprints, with temporal extensions. Based on the temporal property graph, we present and prototype the publish-subscribe architecture, which enables to publish graph elements and notify the processed graph elements of interest to subscribers on the fly.
['Jaewook Byun', 'Sungpil Woo', 'Daeyoung Kim']
Hairspring: Online graph processing middleware for temporal networks