A Middleware for Data-centric and Dynamic Distributed Complex Event Processing for IoT Real-time Analytics in the Cloud
Abstract. IoT big data real-time analytics systems need to effectively process and manage massive amounts of data from streams produced by distributed data sources. There are many challenges in deploying and managing processing logic at execution time in those systems, especially when 24x7 availability is required. Aiming to address those challenges, we have developed and tested a middleware for Distributed CEP, with a data-centric and dynamic design, based on the Data Distribution Service for Real- Time Systems (OMG-DDS) specification and its extension for dynamic topics/types (DDS-XTypes). Its main advantages include the use of OMG-DDS; witch is suitable for IoT applications with QoS requirements, its dynamic capabilities, and the scalable and parallel execution of the CEP rules on a dynamic set of processing nodes.
