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Optimizing the Performance of Automated Business Processes Executed on Virtualized Infrastructure




Published: 2014 Januar
Herausgeber: IEEE
Buchtitel: Proceedings of the 47th Hawai'i International Conference on System Sciences (HICSS)
Seiten: 3818-3826
Verlag: IEEE
Erscheinungsort: Waikoloa, HI
Organisation: IEEE
Referierte Veröffentlichung
Note: conditionally accepted.
BibTeX

Kurzfassung
With few exceptions, the opportunities cloud com-puting offers to business process management (BPM) technologies have been neglected so far. We investi-gate opportunities and challenges of implementing a BPM-aware cloud architecture for the benefit of pro-cess runtime optimization. Processes with predomi-nantly 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.


Projekt

DAAD PPP Australia (Sydney)



Forschungsgruppe

Ökonomie und Technologie der eOrganisation


Forschungsgebiet
Cloud Computing, Business Activity Management, Geschäftsprozessmanagement