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The interoperability of Web services has resulted in its adoption for recently-emerging cloud platforms. SOAP (Simple Object Access Protocol) is considered as the main platform independent communication tool for the Cloud Web service. Generally, Cloud Web services suffer performance bottlenecks and congestions that are mainly caused by the encoding of XML messages as they are bigger than the real payloads. In this paper, Fractal clustering model is proposed to compute the Fractal clustering similarity of SOAP messages in order to cluster them and enable the aggregation of SOAP messages to significantly reduce the size of the aggregated SOAP messages. Furthermore, as Fractal is a well-known as a time-consuming technique especially for large dataset, two fast Fractal clustering models have been proposed that are aiming to reduce the required clustering time. The proposed fast Fractal models have tremendously outperformed the classical Fractal model in terms of the processing time and have outperformed both K-means and PCA combined with K-means models in terms of both the processing time and SOAP messages size reduction.