Large-scale computational resources are increasingly being delivered through distributed clusters of commodity workstations, which, when taken as a whole, provide the raw horsepower of traditional supercomputers at significantly reduced cost. Unfortunately, economic reality still dictates that large clusters must be shared across multiple, distinct applications, each with their own resource needs. This project focuses on designing and implementing an efficient management framework that enables the creation, allocation, and management of virtual clusters.
A logical abstraction layered on top of a set of physical machines, virtual clusters harness virtual machine technology to more efficiently share computational resources between competing application demands while ensuring fault isolation. Critically, this proposal leverages the power of virtual machine monitors to provide novel functionality for an emerging class of applications. In particular, by exposing the dynamic levels of parallelism, dilating logical time, and supporting apparently infinitely large clusters, this work supports the distinctive needs of grid computing, network modeling, and Internet epidemiology.
An output of this work will be a fully operational environment for managing cluster-based computational resources integrated with publicly available virtual machine technology. In addition to dynamically adjusting resources in response to changes in demand and application load, virtual clusters can instantly create clones of existing virtual machines, a functionality critical to the deployment of large-scale high-fidelity honeypots. Finally, the ability to slow down logical time within a virtual cluster---thereby speeding up the relative speed of network communication---enables the emulation of network links orders of magnitude faster than those typically available on commodity clusters.
