Process Discovery from Event Stream Data in the Cloud - A Scalable, Distributed Implementation of the Flexible Heuristics Miner on the Amazon Kinesis Cloud Infrastructure

摘要

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.