# QoS-Based Pattern Recognition Approach for Web Service Discovery: Ar_WSDS
## 7 Discussion  
WS discovery and selection in cloud environments has generated interest in complying with quality requirements, thus offering users high-performance services and better access to providers. We tested our approach to obtain an overview of the behavior of services and the dynamic change in their QoS parameters, which differed significantly from the provider in which it is deployed. The redundancy inserted in the data set showed the differences between the services discovered and those selected. Thus, the execution time of the Ar_WSDS computational strategy increased as a function of the number of replicated WSs. However, under a natural environment, these scenarios can identify services with updated information having marked differences between their QoS, where the recognition provided by Ar_WSDS can result in considerable execution time improvements. We consider the ACM as a problem in a sequential workflow; however, there are several types of workflows: selection workflow, parallel workflow, and cycle workflow; these depend mainly on a global QoS (QoS parameters that the composite service must have), these workflows through techniques can be converted to sequential workflows, processes that can generate more than one workflow for an ACM. The majority of solutions reported in the literature use QoS global [2; 6; 16; 31], and how services contribute to achieving the objective, our system instead evaluates each service at the level of personalization of its QoS. The QoS global is taken as a quality value to be achieved by each solution path (set of candidate services for each node of the composition) created by our system. This type of adaptation allows for improved monitoring of the NFR of individual services. This feature is denoted in dynamic compositions that require structural changes in the functionality of a composite service without altering the FR for which it was created. Figure 11 compares the recognition by key and partial signals using the average of the solution paths found for two, four, and nine active signals. Consequently, when the number of signals increased, the number of SP decreased. This situation occurred as the value of paths discovered by key signals was lower because this type of recognition is more restrictive and depends on the process executed in the \(\Gamma\) module, according to the QoS type. As the QoS parameters increase for selection, the discovery space shrinks. Thus, finding the SP for the input composition model will be performed with efficient runtimes, compared to solutions with sequential searches or detailed analyses for each QoS. \begin{table}
\begin{tabular}{c c c c c} \hline \hline
**WS ID** & **Ar\_WSDS** & **Ar\_WSDS** & **OAEQoS** & **GDSA** \\  & **Key** & **Partial** & & \\ \hline
1 & 0 & 1 & 2 & 16 \\
2 & 0 & 0 & 0 & 4 \\
3 & 0 & 0 & 2 & 13 \\
5 & 1 & 0 & 2 & 4 \\
6 & 0 & 0 & 1 & 3 \\
7 & 0 & 0 & 0 & 3 \\
8 & 0 & 0 & 2 & 5 \\
9 & 0 & 0 & 1 & 1 \\ \hline \hline \end{tabular}
\end{table} 
Table 9: Amount of errors in the selection of services. The QoS parameters may vary; however, there are cases where the similarity of values makes choosing a service complicated. Ar_WSDS, using its recognition modules, can analyze all the parameters and find the differences between their values, thus allowing for the differentiation of a service from others. Table 5 displays this situation, where the similarity of QoS parameters for BINDService and DOTSGoePhone services are described using only three parameters. Tests performed in the case study demonstrated the effectiveness of the recognition process, in its two stages, by key or partial signals. Table 6 shows how it is necessary to specify the thresholds for key recognition, which means that the programmer must know the desired QoS parameters in advance; however, partial recognition offers the advantage of analyzing all WSs and obtaining the most appropriate ones, providing a more comprehensive range of SPs for selecting services.