# Survey on Quality of Experience Evaluation for Cloud-Based Interactive Applications
## 6 Stages of the Quantification of QoE in CIAs
### Processing Stage: Computing QoE  
Here, we present a classification of how the proposals in the literature process the input stage metrics:  
* Ad hoc heuristics: Processing techniques created to obtain an output metric that is not generalizable to objectives other than the quantification of QoE in CIAs. * Image processing: A set of techniques applied to digital images to transform them or extract features. * Artificial intelligence: Processing techniques that use a set of training data to automatically build a model. Table 6 summarises the proposals presented in Section 5 and groups them by processing technique. Some proposals use multiple processing techniques simultaneously. Processing techniques based on ad hoc heuristics varied. Some proposals calculated ratios from the input metrics, related several of them through regression techniques or mathematical adjustments, or directly thresholded one or more of the input metrics based on studies that related their thresholds to QoE degradation. On the other hand, other works used the metric obtained through processing as the representative value of the QoE assessment. In these techniques, researchers did not determine whether a processing metric was sufficient to guarantee QoE. These works were based on the hypothesis that optimising \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Ref.** & \begin{tabular}{c} **Ad Hoc** \\ **Heuristics** \\ \end{tabular} & \
\begin{tabular}{c} **Image** \\ **Processing** \\ \end{tabular} &
\begin{tabular}{c} **Artificial** \\ **Intelligence** \\ \end{tabular} \\ \hline [PERSON] et al. (2003) [49] & Yes & & \\ \hline [PERSON] et al. (2011) [43] & Yes & & \\ \hline [PERSON] et al. (2014) [31] & Yes & Yes & \\ \hline [PERSON] et al. (2015) [51] & Yes & & \\ \hline [PERSON] et al. (2017) [46] & & Yes & \\ \hline [PERSON] et al. (2018) [52] & & Yes & \\ \hline [PERSON] et al. (2018) [38] & Yes & & \\ \hline [PERSON] et al. (2018) [44] & Yes & & \\ \hline [PERSON] et al. (2018) [53] & Yes & & \\ \hline [PERSON] et al. (2019) [42] & & Yes & \\ \hline [PERSON] et al. (2019) [40] & Yes & & \\ \hline [PERSON] (2019) [57] & & Yes & \\ \hline [PERSON] et al. (2019) [33] & Yes & & \\ \hline [PERSON] et al. (2019) [54] & Yes & & \\ \hline [PERSON] et al. (2019) [41] & Yes & & \\ \hline [PERSON] et al. (2020) [36] & Yes & & \\ \hline Nvidia (2020) [58] & Yes & & \\ \hline [PERSON] et al. (2020) [35] & Yes & Yes & Yes \\ \hline [PERSON] et al. (2020) [47] & & & Yes \\ \hline Leo Bodnar Electronics (2021) [55] & Yes & & \\ \hline Leo Bodnar Electronics (2021) [56] & Yes & & \\ \hline [PERSON] et al. (2021) [39] & & Yes & \\ \hline [PERSON] et al. (2021) [50] & & Yes & \\ \hline [PERSON] et al. (2021) [48] & Yes & & \\ \hline [PERSON] et al. (2021) [34] & & Yes & \\ \hline [PERSON] et al. (2021) [9] & Yes & & \\ \hline [PERSON] et al. in [37] & Yes & & \\ \hline Exoprise (2024) [45] & & Yes & \\ \hline \hline \end{tabular}
\end{table} 
Table 6: Proposals from the literature and the processing techniques used. the obtained metrics (maximising or minimising, as the case may be) is a measure for guaranteeing sufficient QoE to users. Processing techniques based on image processing used digital images or image sequences as inputs. These processing techniques also varied. Some proposals involved comparing images to determine if they were the same, calculating degradations, or identifying modifications in different elements of a CIA's architecture. Authors achieve this by comparing the bitmaps of an image pixel by pixel or using discriminators to check whether they match previously stored reference images. Some proposals calculated hashes (MD5, CRC, SHA-1, etc.) for discriminators, while others modified the processed images to insert an encoding that allows for unequivocal identification of each image or frame, differentiating one from the others with unique identifiers. These identifiers enable the tools to determine whether two images are the same without the need to check all their pixels.