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Visualization of complex 3D objects is a task that can be required by a large number of applications. For instance, IBM provides (remote) visualization frameworks for petroleum engineering, while SGI supplies complete workflow solutions for (remotely) visualizing simulation environments tailored to specific scenarios, including fluid dynamics, structural mechanics, etc. Moreover, in the industrial sector, graphics environments (often involving also mobile devices) are exploited in order to assist maintenance engineers on the factory floor (Goose et al. 2003).
Basically, two main approaches can be adopted in order to visualize a 3D scene: the scene is stored and processed locally on the same device where it is displayed, or the scene is remotely stored and processed and a 2D representation of the underlying 3D data is delivered to the device in charge of carrying out the visualization. The first solution can generally involve large storage space and high computational power which are not always available on “thin” terminals such as mobile devices. On the other hand, with the remote visualization approach, the geometry to be visualized can be maintained on a remote server able to cope with (complex) 3D models. Although this characteristic is positive in terms of data security, it involves – in general – the transmission of a large amount of data over the network.
The remote visualization paradigm can be implemented using two different approaches. In the first one, the whole desktop is sent to the client device. The main limitation of this solution is that it does not provide an optimal support for small displays (Richardson et al. 1998). In the second approach, ad hoc frameworks are designed and implemented with the aim of allowing the client device to directly control the remote application interface and to receive back, as a result, the content of the working area (Lamberti & Sanna 2007; Stegmaier et al. 2003).
Regardless of the specific approach being considered, when the Quality of Service (QoS) of the network connection supporting the remote visualization application cannot be negotiated and established in advance, aspects related to Quality of Experience (QoE) have to be taken into account. Furthermore, it is worth observing that even network connections providing a high QoS can result in a poor QoE when user expectations are not fully met. Thus, on the one hand QoS represents the ability of a network to provide a service with a guaranteed level of performance and on the other it describes how the service is perceived by the user and the associated satisfaction degree on the user side. QoE can be seen as an extension of the traditional QoS in the sense that QoE provides information regarding the delivered services from an end-user point of view (Van Moorsel 2001). The main differences between QoS and QoE are summarized in Table 1.
Table 1. QoS | QoE |
Related to objective parameters | Related to user perception (subjective) |
Measurable, in general, with good precision | Estimable in an approximate way |
Evaluated a priori | Evaluated in retrospect |
Indicating the quality delivered | Indicating the quality perceived |