Many language resources are being shared as web services to process data on the Internet. As dataset size keeps growing, language services are experiencing more big data problems, such as the storage and processing overheads caused by the huge amounts of multilingual texts. Parallel execution and cloud technologies are the keys to making service invocation practical. In the Service-Oriented Architecture approach, service providers typically employ policies to limit parallel execution of the services based on arbitrary decisions. In order to attain optimal performance, users need to adapt to the services policies. A composite service is a combination of several atomic services provided by various providers. To use parallel execution for greater composite service efficiency, the degree of parallelism (DOP) of the composite services need to be optimized by considering the policies of all atomic services. We propose a model that embeds service policies into formulae and permits composite service performance to be calculated. From the calculation results, we can predict the optimal DOP for the composite service that allows the best performance to be attained. Extensive experiments are conducted on real-world translation services. The analysis results show that our proposed model has good prediction accuracy in identifying optimal DOPs for composite services.