Towards a Scalable Cloud-based RDF Storage Offering a Pub/Sub Query Service

Recently, Complex Event Processing engines have gained more and more interest. Their purpose consists in combining realtime and historical data in addition to knowledge bases to deduce new information. Also, RDF is now commonly used to make information machine-processable. In this short paper we propose to leverage existing research about distributed storage and realtime filtering of RDF data with the intention of helping Complex Event Processing engines to reach their goal at large scale. Towards this objective, we identify and discuss the challenges that have to be addressed for providing a solution that supports RDF data storage and a pub/sub retrieval service on a cloud-based architecture. Then, we explain how to meet these challenges through a solution based on structured Peer-to-Peer networks. Finally, we discuss the status of our ongoing work whose implementation is realized thanks to ProActive, a middleware for programming cloud-based distributed applications.