Argonne National Laboratory

Combining Batch Execution and Leasing Using Virtual Machines

TitleCombining Batch Execution and Leasing Using Virtual Machines
Publication TypeConference Paper
Year of Publication2007
AuthorsSotomayor, B, Keahey, K, Foster, IT
Date Published12/2007
Other NumbersANL/MCS-P1491-0408

As cluster computers are used for a wider range of applications, we encounter the need to deliver resources at particular times, to meet
particular deadlines, and/or at the same time as other resources are
provided elsewhere. To address such requirements, we describe a scheduling approach in which users request resource leases, where
leases can request either as-soon-as-possible (“best-effort”) or reservation start times. We present the design of a lease management
architecture, Haizea, that implements leases as virtual machines
(VMs), leveraging their ability to suspend, migrate, and resume
computations and to provide leased resources with customized application environments. We discuss methods to minimize the overhead
introduced by having to deploy VM images before the start of a lease. We also present the results of simulation studies that compare alternative approaches. Using workloads with various mixes of best-effort and advance reservation requests, we compare the performance of our VM-based approach with that of non-VMbased
schedulers. We find that a VM-based approach can provide better performance (measured in terms of both total execution time and average delay incurred by best-effort requests) than a scheduler
that does not support task pre-emption, and only slightly worse performance than a scheduler that does support task pre-emption. We
also compare the impact of different VM image popularity distributions
and VM image caching strategies on performance. These results emphasize the importance of VM image caching for the workloads studied and quantify the sensitivity of scheduling performance to VM image popularity distribution.