[Zurück]

P. Waibel, A. Yeshchenko, S. Schulte, J. Mendling:
"Optimized Container-Based Process Execution in the Cloud";
Vortrag: 26th International Conference on Cooperative Information Systems (CoopIS 2018), Valletta, Malta; 24.10.2018 - 26.10.2018; in: "On the Move to Meaningful Internet Systems: OTM 2018 Conferences - Confederated International Conferences: CoopIS, C&TC, and ODBASE 2018, Proceedings, Part II", H. Panetto, C. Debruyne, H. Proper, C. Ardagna, D. Roman, R. Meersman (Hrg.); Springer, Cham, LNCS 11230 (2018), ISBN: 978-3-030-02670-7; S. 3 - 21.

A key challenge for elastic business processes is the resource-efficient scheduling of cloud resources in such a way that Quality-of-Service levels are met. So far, this has been difficult, since existing approaches use a coarse-granular resource allocation based on virtual machines.
In this paper, we present a technique that provides fine-granular resource scheduling for elastic processes based on containers. In order to address the increased complexity of the respective scheduling problem, we develop a novel technique called GeCo based on genetic algorithms. Our evaluation demonstrates that in comparison to a baseline that follows an ad hoc approach a cost saving between 32.90% and 47.45% is achieved by GeCo while considering a high service level.

Elastic processes · Optimization · Scheduling Business process management · Software containers

http://dx.doi.org/10.1007/978-3-030-02671-4_1