Capacity Leasing in Cloud Systems using the OpenNebula Engine

Clouds can be used to provide on-demand capacity as a utility. Although the realization of this idea can differ among various cloud providers (from Google App Engine to Amazon EC2), the most flexible approach is the provisioning of virtualized resources as a service. These virtualization-based clouds, like Amazon EC2 or the Science Clouds (which uses the Globus Virtual Workspace Service [4]), provide a way to build a large computing infrastructure by accessing remote computational, storage and network resources. Since a cloud typically comprises a large amount of virtual and physical servers, in the order of hundreds or thousands, efficiently managing this virtual infrastructure becomes a major concern. Several solutions, such as VMWare VirtualCenter, Platform Orchestrator, or Enomalism, have emerged to manage virtual infrastructures, providing a centralized control platform for the automatic deployment and monitoring of virtual machines (VMs) in resource pools. However, these solutions provide simple VM placement and load balancing policies. In particular, existing clouds use an immediate provisioning model, where virtualized resources are allocated at the time they are requested, without the possibility of requesting resources at a specific future time and, at most, being placed in a simple first-come-first-serve queue when no resources are available. However, service provisioning clouds, like the one being built by the RESERVOIR project, have requirements that cannot be supported within this model, such as resource requests that are subject to non-trivial policies, capacity reservations at specific times to meet peak capacity requirements, variable resource usage throughout a VM’s lifetime, and dynamic renegotiation of resources allocated to VMs. Additionally, smaller clouds with limited resources, where not all requests may be satisfiable immediately for lack of resources, could benefit from more complex VM placement strategies supporting queues, priorities, and advance reservations. In this work we explore extending the capacity provisioning model used in current clouds by using resource leases [3, 10, 9] as a fundamental provisioning abstraction. To do this, we have integrated the OpenNebula virtual infrastructure engine with the Haizea lease manager to produce a resource management system that can be used to support a variety of leases in clouds. We focus in this work on advance reservation leases, which can be used to satisfy capacity peaks known in advance, or for a variety of well-documented use cases where advance reservations are used (such as coscheduling of multiple resources [12, 5, 1, 2], urgent