Policy-Aware Optimization of Parallel Execution of Composite Services

Parallel execution and cloud technologies are the keys to speed-up service invocation when processing large-scale data. In SOA, service providers normally employ policies to limit parallel execution of the services based on arbitrary decisions. In order to attain optimal performance improvement, service users need to adapt to parallel execution policies of the services. A composite service is a combination of several atomic services provided by various providers. To use parallel execution for greater composite service efficiency we need to optimize the degree of parallelism (DOP) of the composite services by considering policies of all atomic services. We propose a model that embeds service policies into formulae to calculate composite service performance. From the calculation, we predict the optimal DOP for the composite service. Extensive experiments are conducted on real-world translation services. The results show that our proposed model has good prediction accuracy in identifying the optimal DOPs. Our model correctly predicts the optimal DOP in most cases.