Availability, Performance and Cost Analysis for Large Scale Cloud

We believe that research is needed in scalable methods for the availability, performance, energy consumption, resiliency and cost analysis of cloud systems through high fidelity analytic models and optimization. Cloud based systems are inherently large scale, distributed, almost always virtualized, and operate in automated shared environments. Performance and availability of such systems are affected by a large number of parameters including characteristics of the physical infrastructure (e.g., number of servers, number of cores per server, amount of RAM and local storage per server, configuration of physical servers, network configuration, persistent storage configuration), characteristics of the virtualization infrastructure (e.g., VM placement and VM resource allocation, deployment and runtime overheads), failure characteristics (e.g., failure rates, repair rates, modes of recovery), characteristics of automation tools used to manage the cloud system, and so on. Because of this, any naive modeling approach will quickly run into state explosion and/or intractable solution. Scale of the cloud makes the problems challenging in terms developing practical solutions. Unfortunately, above described challenges are not currently addressed or are addressed in an ad hoc manner. A few measurement based approaches and simple analytic and simulation models that do not capture the details o