The Study On Performance Optimization Of Web Service

Web services are popularly used on the network, and have been emerged as a powerful mechanism for integrating disparate IT systems and assets. Web Services use XML to describe the interfaces and to transfer the messages. XML-based Web Services communicate over standard Web protocols using XML interfaces and XML messages, which any application can interpret. But the verbosity inherent in XML encoding may cause performance problems in some classes of applications and in resource-constrained environments. In this paper, the optimization solutions of Web Services performance is focused and studied based on the analysis of the main reasons of the performance bottlenecks.The concept of optimized efficiency is presented, and then an optimized efficiency model is identified for easy comparing the optimized results of different technologies. The type of services needs different requirement of performance. So services are divided from different points and a service type model is designed, which can be a reference for choosing the right optimization solution. In this paper, three optimization strategies are designed that are object optimization, combined optimization and step optimization. The strategies consider the implementation of optimization from different points. Then a chain-based optimized solution is given based on the three strategies. This solution combines the strategies together and makes the optimization process like a chain that including several handlers to adopt technologies to optimize performance in different steps. This solution meets the requirement of web services performance optimization to a certain extent.The technologies that referenced by the optimization solution are designed and implemented such as Gzip compression, differential serialization, attachment and cache. In this paper, cache is studied deeply and optimized with priority-based cache control method.Finally, a test case is built for testing the effect of the chain-based optimizing solution. The test data is presented for comparing different optimizing efficiency and show that this solution can improve the performance.