Jim Pruyne

Utility services providers offer on-demand services for multiple users and applications from a shared resource pool. The utility computing environment provider manages resources that have multiple dimensions, namely CPU, Memory and Disk. It is important that a mechanism of quantification he utilized for determining pricing. Also in these environments, we believe that price needs to be adapted to reflect and influence dynamic change in demand on resources, and can be used, as an economic mechanism, to efficiently manage a utility computing environment. To achieve this, we propose in this paper an adaptive pricing mechanism. The objective of this scheme is twofold: it, for business objectives, adapts price based upon the supply and demand curves over time intervals; on the other hand, price invisibly manages the distribution of resource demand across time intervals, therefore makes resource utilization more efficient and balanced over time. In this approach, the resource unit to be priced is called capacity unit, and applications are billed based upon the capacity units that have been reserved or used.

Shared services, hosted in utility computing environments are becoming quite common in enterprises. These services could be clusters of application servers hosting various applications or even clusters of databases catering to multiple organizations within an enterprise. Automating the provisioning of these shared services is a difficult problem. We propose a model-based automation mechanism to provision such shared services. We demonstrate our model-based provisioning system in the case of a shared desktop service. The shared desktop service termed the "virtual desktop system" (VDS) hosts desktops on top of virtual machines. These desktop virtual machines are provisioned on consolidated data centers while users use thin clients to connect to their "virtual" desktops. We demonstrate how we use our model-based automation technique to simplify the provisioning of such desktops.