Enhanced web services performance by compression and similarity-based aggregation of SOAP traffic

Many organizations around the world have adopted Web services, server farms hosted by large enterprises, and data centres for various applications. Web services offer several advantages over other communication technologies. However, it still has high latency and often suffers congestion and bottlenecks due to the massive load generated by large numbers of end users for Web service requests. Simple Object Access Protocol (SOAP) is the basic Extensible Markup Language (XML) communication protocol of Web services that is widely used over the Internet. SOAP provides interoperability by establishing access among Web servers and clients from the same or different platforms. However, the verbosity of the XML format and its encoded messages are often larger than the actual payload, causing dense traffic over the network. This thesis is proposing three innovative techniques capable of reducing small, as well as very large, messages. Furthermore, new redundancy-aware SOAP Web message aggregation models (Binary-tree, Two-bit, and One-bit XML status trees) are proposed to enable the Web servers to aggregate SOAP responses, and send them back as one compact aggregated message, thereby reducing the required bandwidth and latency, and improving the overall performance of Web services. Fractal as a mathematical model provides powerful self-similarity measurements for the fragments of regular and irregular geometric objects in their numeric representations. Fractal mathematical parameters are introduced to compute SOAP message similarities that are applied on the numeric representation of SOAP messages. Furthermore, SOAP fractal similarities are developed to devise a new unsupervised auto-clustering technique. Fast fractal similarity based clustering technique is proposed with the aim of speeding up the computations for the selection of similar messages to be aggregated together in order to achieve greater reduction