Abstract
Desktop clouds (DC) provide services in non-stationary environments that face reliability and performance threats not found in traditional clusters and datacenters. The idle resources available on computers can be claimed by users, turned off and faulted any time. For instance, platforms such as CernVM and UnaCloud harvest idle resources on computer labs to run virtual machines and support scientific applications. These platforms deal with interruptions and interferences caused by both users and applications. This non-stationarity is one of the main sources of issues in the design of reliable desktop cloud infrastructures that are capable of mitigating their own faults and errors. Based on a fault analysis that we have been carrying out and refining for a couple of years, we have found that reliability problems begin as the number of virtual machines that are going to be executed increases; these virtual machines must first be provisioned in the physical machines where they will be hosted. On the one hand, the main factors that can affect the provisioning of virtual machines in a DC are: the use of disk space, and the transmission of virtual images over the network. On the other hand, the applications and actions performed by users in the desktops may cause the virtual machine malfunction. In this paper, we propose an strategy based on known techniques applied to a particular environment: the scalable provisioning of virtual machines in desktop clouds. In addition, we describe the implementation and analyze its effectiveness.
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Acknowledgments
We would like to thank David Camilo Bonilla Verdugo for all his collaboration running the experiments discussed in this paper.
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Gómez, C.E., Chavarriaga, J., Tchernykh, A., Castro, H.E. (2020). Improving Reliability for Provisioning of Virtual Machines in Desktop Clouds. In: Schwardmann, U., et al. Euro-Par 2019: Parallel Processing Workshops. Euro-Par 2019. Lecture Notes in Computer Science(), vol 11997. Springer, Cham. https://doi.org/10.1007/978-3-030-48340-1_51
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DOI: https://doi.org/10.1007/978-3-030-48340-1_51
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