Simulating Dynamic Cloud Marketspaces: Modeling Spot Instance Behavior and Scheduling with CloudSim Plus

The increasing reliance on dynamic pricing models, such as spot instances, in public cloud environments presents new challenges for workload scheduling and reliability. While these models offer cost advantages, they introduce volatility and uncertainty that are not fully addressed by current allocation algorithms or simulation tools. This work contributes to the modeling and evaluation of such environments by extending the CloudSim Plus simulation framework to support realistic spot instance lifecycle management, including interruption, termination, hibernation, and reallocation. The enhanced simulator is validated using synthetic scenarios and large-scale simulations based on the Google Cluster Trace dataset. Building on this foundation, the HLEM-VMP allocation algorithm, originally proposed in earlier research, was adapted to operate under dynamic spot market conditions. Its performance was evaluated against baseline allocation strategies to assess its efficiency and resilience in volatile workload environments. The comparison demonstrated a reduction in the number of spot instance interruptions as well as a decrease in the maximum interruption duration. Overall, this work provides both a simulation framework for simulating dynamic cloud behavior and analytical insights into virtual machine allocation performance and market risk, contributing to more robust and cost-effective resource management in cloud computing.