An Approach for Efficiently Combining Real-Time and Past Events for Ubiquitous Business Processing

Abstract

Nowadays, datasets become larger and larger. As stated by Eric Schmidt, every two days now we create as much or more information as we did from the dawn of civilization up until 2003. Thus, the question is how to make good use of such big data. A solution is Complex Event Processing (CEP) engines that propose to correlate realtime, contextual and past information. In this paper we propose a new architecture that leverages existing research done in Publish/Subscribe systems and CEP engines with the idea to federate them in order to scale to the load that could be encountered in todays ubiquitous events workloads.