Optimizing the Performance of Automated Business Processes Executed on Virtualized Infrastructure
Christian Janiesch, Ingo M. Weber, Jörn Kuhlenkamp, Michael Menzel · 2014
With few exceptions, the opportunities cloud computing offers to business process management (BPM) technologies have been neglected so far. We investigate opportunities and challenges of implementing a BPM-aware cloud architecture for the benefit of process runtime optimization. Processes with predominantly automated tasks such as data transformation processes are key targets for this runtime optimization. In theory, off-the-shelf mechanisms offered by cloud providers, such as horizontal scaling, should already provide as much computational resources as necessary for a process to execute in a timely fashion. However, we show that making process data available to scaling decisions can significantly improve process turnaround time and better cater for the needs of BPM. We present a model and method of cloud-aware business process optimization which provides computational resources based on process knowledge. We describe a performance measurement experiment and evaluate it against the performance of a standard automatic horizontal scaling controller to demonstrate its potential.