Dynamic workflow scheduling (DWS) plays a crucial role in cloud computing. This simulator aims to make intelligent decisions in terms of workflow allocation and VM provisioning by VM selection rules (VMSRs). The objective is to minimize the total costs associated with VM rental fees and deadline violation penalties. Certainly, the objective function can also be customized according to needs.
File Name | Description |
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MAIN-OneTimeSimulation.py | Evaluate a problem instance (with 30 workflows) using a randomly generated VM selection rule (in form of a GP tree) |
MAIN-SGP.py | Using single-tree GPHH (SGP) to solve dynamic workflow scheduling problems, and individuals in each generation are evaluated on multiple problem instances. Training and test phases integrated into this file |