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Speech with CD or web proceedings
By moving business processes into the cloud,<br> business partners can benefit from lower costs, more flexibility<br> and greater scalability in terms of resources offered by the<br> cloud providers. In order to execute a process or a part of it, a<br> business process owner selects and leases feasible resources<br> while considering different constraints; e.g., optimizing resource<br> requirements and minimizing their costs. In this context,<br> utilizing information about the process models or the dependencies<br> between tasks can help the owner to better manage<br> leased resources. In this paper, we propose a novel resource<br> allocation technique based on the execution path of the process,<br> used to assist the business process owner in efficiently leasing<br> computing resources. The technique comprises three phases,<br> namely process execution prediction, resource allocation and<br> cost estimation. The first exploits the business process model<br> metrics and attributes in order to predict the process execution<br> and the required resources, while the second utilizes this<br> prediction for efficient allocation of the cloud resources. The<br> final phase estimates and optimizes costs of leased resources by<br> combining different pricing models offered by the provider.
Information and Communication Technology
2015 IEEE World Congress on Services
<u>T. Mastelic</u>, W. Fdhila, I. Brandic, S. Rinderle-Ma: <br>"<i><a href="http://dx.doi.org/10.1109/SERVICES.2015.16" target="_blank" class="publist">Predicting Resource Allocation and Costs for Business Processes in the Cloud</a></i>"; <br>Talk: IEEE 11th World Congress on Services (SERVICES 2015), New York, USA; 06-27-2015 - 07-02-2015; in: "<i>2015 IEEE World Congress on Services</i>", (2015), ISBN: 978-1-4673-7275-6; 8 pages.<br><br> <a href="https://publik.tuwien.ac.at/showentry.php?ID=240257&lang=2" class="publist"><i>More information</i></a><br><br>