Overhead-Aware-Best-Fit (OABF) Resource Allocation Algorithm for Minimizing VM Launching Overhead
FermiCloud is a private cloud developed in Fermi National Accelerator Laboratory to provide elastic and on-demand resources for different scientific research experiments. The design goal of the FermiCloud is to automatically allocate resources for different scientific applications so that the QoS required by these applications is met and the operational cost of the FermiCloud is minimized. Our earlier research shows that VM launching overhead has large variations. If such variations are not taken into consideration when making resource allocation decisions, it may lead to poor performance and resource waste. In this paper, we show how we may use an VM launching overhead reference model to minimize VM launching overhead. In particular, we first present a training algorithm that automatically tunes a given refer- ence model to accurately reflect FermiCloud environment. Based on the tuned reference model for virtual machine launching overhead, we develop an overhead-aware-best-fit resource allocation algorithm that decides where and when to allocate resources so that the average virtual machine launching overhead is minimized. The experimental results indicate that the developed overhead-aware-best-fit resource allocation algorithm can significantly improved the VM launching time when large number of VMs are simultaneously launched.
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- OSTI Identifier:
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- Research Org:
- Fermi National Accelerator Laboratory (FNAL), Batavia, IL (United States)
- Sponsoring Org:
- USDOE Office of Science (SC), High Energy Physics (HEP) (SC-25)
- Country of Publication:
- United States
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