Multifaceted Resource Management on Virtualized Providers

Last decade, providers started using Virtual Machines (VMs) in their datacenters to pack users and their applications. This was a good way to consolidate multiple users in fewer physical nodes while isolating them from each other. Later on in 2006, Amazon started offering their Infrastructure as a Service where their users rent computing resources as VMs in a payas-you-go manner. However, virtualized providers cannot be managed like traditional ones as they are now confronted with a set of new challenges. First of all, providers must deal efficiently with new management operations such as the dynamic creation of VMs. These operations enable new capabilities that were not there before, such as moving VMs across the nodes, or the ability to checkpoint VMs. We propose a Decentralized virtualization management infrastructure to create VMs on demand, migrate them between nodes, and checkpointing mechanisms. With the introduction of this infrastructure, virtualized providers become decentralized and are able to scale. Secondly, these providers consolidate multiple VMs in a single machine to more efficiently utilize resources. Nevertheless, this is not straightforward and implies the use of more complex resource management techniques. In addition, this requires that both customers and providers can be confident that signed Service Level Agreements (SLAs) are supporting their respective business activities to their best extent. Providers typically offer very simple metrics that hinder an efficient exploitation of their resources. To solve this, we propose mechanisms to dynamically distribute resources among VMs and a resource-level metric, which together allow increasing provider utilization while maintaining Quality of Service. Thirdly, the provider must allocate the VMs evaluating multiple facets such as power consumption and customers’ requirements. In addition, it must exploit the new capabilities introduced by virtualization and manage its overhead. Ultimately, this VM placement must minimize the costs asso-