Abstract
When simulating reference nets, the size (places, transitions; memory and CPU consumption) of the simulation is usually not known before actual runtime. This behavior originates from the concept of net instances, which are similar to objects in object-oriented programming. The simulator Renew supports very basic distribution but the manual infrastructural setup for simulations exceeding the capabilities of one machine is left up to the modeler until now. In this work the RenewKube tool, a ready to use Kubernetes and Docker based solution, is presented, that allows to control automated scaling of simulation instances from within the net running in the Renew simulator.
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Notes
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size refers to utilized CPU, RAM usage and also (but not primarily) hard disk usage.
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In recent implementations there is Windows support as well.
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For definition of up- and downlinks see Sect. 2.
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Headless in this context refers to running without graphical user interface.
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Röwekamp, J.H., Moldt, D. (2019). RenewKube: Reference Net Simulation Scaling with Renew and Kubernetes. In: Donatelli, S., Haar, S. (eds) Application and Theory of Petri Nets and Concurrency. PETRI NETS 2019. Lecture Notes in Computer Science(), vol 11522. Springer, Cham. https://doi.org/10.1007/978-3-030-21571-2_4
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