A key advantage of Infrastructure-as-a-Service (IaaS) clouds is providing users on-demand access to resources. However, to provide on-demand access, cloud providers must either significantly overprovision their infrastructure (and pay a high price for operating resources with low utilization) or reject a large proportion of user requests (in which case the access is no longer on-demand). At the same time, not all users require truly on-demand access to resources.
Many applications and workflows are designed for recoverable systems where interruptions in service are expected. For instance, many scientists utilize High Throughput Computing (HTC)-enabled resources, such as Condor, where jobs are dispatched to available resources and terminated when the resource is no longer available.
We propose a cloud infrastructure that combines on-demand allocation of resources with opportunistic provisioning of cycles from idle cloud nodes to other processes by deploying backfill Virtual Machines (VMs). For demonstration and experimental evaluation, we extend the Nimbus cloud computing toolkit to deploy backfill VMs on idle cloud nodes for processing an HTC workload.
Initial tests show an increase in IaaS cloud utilization from 37.5% to 100% during a portion of the evaluation trace but only 6.39% overhead cost for processing the HTC workload.
We demonstrate that a shared infrastructure between IaaS cloud providers and an HTC job management system can be highly beneficial to both the IaaS cloud provider and HTC users by increasing the utilization of the cloud infrastructure (thereby decreasing the overall cost) and contributing cycles that would otherwise be idle to processing HTC jobs
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