MMEA Platform Harri Hytönen (Vaisala) September 23, 2015

Satellite Radar In-situ Modelling Citizen science Research

Overview MMEA Platform = scalable real-time data processing with embedded notification, storage, routing, filtering and processing services.

Contributors

OSS Components WSO2 Enterprise Service Bus (ESB) –Integration solution Service virtualization = proxy services Message transformations Transport (HTTP(S)/JMS/SMTP/FTP etc.) switching –Authentication (WSO2 Identity Server) –Authorization –Monitoring and diagnostics

OSS Components Apache ActiveMQ –messaging backbone –quality of service PostgreSQL RDBMS Apache Tomcat Esper –CEP engine Wavellite –framework for situation awareness Octave –High level language for computations Puppet & Artifactory –Deployment tools CentOS

Commercial Components Amazon AWS –EC2 (for hosting) –RDS Profium Sense –RDF storage –Inference engine Confluence & JIRA –Documentation and issue tracking

MMEA Platform Deployment Amazon EC2 binaries config builds source code

Pilot - Indoor Air Quality (VTT, HiQ)

Other Use Cases Helsinki area outdoor air quality Weather stations data ingestion Weather radar product generation Hydrological data ingestion Situational awareness applications –Farmer’s situational awareness –Storm path detection –Semantic end user service

Complex Event Processing Esper –High speed event processing –Identifies meaningful events Targeted to real-time Event Driven Architectures Designed for high-volume event correlation where millions of events coming in would make it impossible to store them all to later query them using classical database architecture Some examples of applications in MMEA: –Detect patterns among events –Filter events and event aggregation –Generating notifications and alerts based on event patterns

Computations in the MMEA platform Mediator

Computation service Computation task 1. Run preprocessor 2. Run Octave script 3. Run postprocessor Workspace Input data and parameters

Thank You – Questions?