This article is based on the book “Creating the Infrastructure for Cloud Computing: An Essential Handbook for IT Professionals”

The virtualization models for clients are, arguably, more diverse than those for servers.  For servers there are essentially two, the earlier model of static consolidation and the more recent dynamic model where virtual machines lightly bound to physical hosts can be moved around with relative ease.

With virtualized clients there are also two main models, depending on whether the application execution takes place in servers in a data center or on the physical client.

But whereas server-based client virtualization services can be delivered through terminal services (session virtualization) or through virtual hosted desktops (virtual desktop infrastructure), client-based virtualization can be delivered through one of five computation models: operating system streaming, remote operating system boot, application streaming (application virtualization), virtual containers and rich distributed computing (rich clients.)  

The first four models are also known as dynamic virtual clients or DVCs, characterized by centrally managed application or operating system images and client-side execution.

Each variant exhibits specific management, security and TCO features. The specific choices are driven by the intended target application scenarios.

At least for server-based clients, their presence may be an indication of technology convergence between clients and server products in cloud space, a continuation of the trend that started when clients were used as presentation devices for traditional three-tier applications.
All the models depend on NAS or SAN storage for accessing operating system images or for operating system or application streaming and delivered through either a desktop or laptop PC or a thin client.

Following are some considerations for evaluating client virtualization solutions.

* Client Devices and Compute Models: Conversations around compute models often get intertwined with the device on which it will be deployed.  The analysis becomes easier if devices and models are treated separately.  For example, the business scenario may dictate server-based computing for a certain application, such as a patient information database.  However, this “thin client” model need not be deployed on a thin terminal.  A desktop or laptop PC may actually be a more appropriate device, depending on a user’s total application and mobility needs.  

* Mixed Compute Models: In most cases, IT will deploy a mix of computation models depending on needs for data security, performance and mobility.  Individual users may have a hybrid of models.  For example, a construction estimator in the field may use a cellular modem to access the centralized job scheduling tool via a terminal server session, but also have Microsoft Office locally installed for word processing and spreadsheet work.

* Benchmarking Applications: There are no industry standard benchmarks for alternative compute models.  Under the current state of the art it is not meaningful to carry out performance comparisons across computation models. IT managers should evaluate performance claims carefully to understand applicability to their situations.

Article by Enrique Castro-Leon, Bernard Golden and Miguel Gomez for .