Publication

Process Discovery in the Cloud – A Scalable, Distributed Implementation of the Flexible Heuristics Miner on the Amazon Kinesis Cloud Infrastructure

Jörg Evermann, Jana-Rebecca Rehse, Peter Fettke

In: Proceedings of the 1st Workshop on Business Process Monitoring and Performance Analysis in the Cloud. Workshop on Business Process Monitoring and Performance Analysis in the Cloud (CloudBPM-2016) located at 8th IEEE International Conference on Cloud Computing Technology and Science December 12-15 Luxemburg Luxembourg IEEE 2016.

Abstract

Cloud computing offers readily available, scalable infrastructure to tackle problems involving high data volume and velocity. Discovering processes from event streams, especially when the business processes execute in a cloud environment, is such a problem. Event stream data is generated rapidly with varying volume and must be processed on-the-fly, making stream processing an important use case for cloud computing. This paper describes a distributed, streaming implementation of the flexible heuristics miner on Amazon Kinesis, a cloud-based event stream infrastructure, showing how mining methods can scale effortlessly to tens of millions of events per minute.

German Research Center for Artificial Intelligence
Deutsches Forschungszentrum für Künstliche Intelligenz