An evaluation of compression and streaming techniques for efficient transfer of XML documents with Simple Object Access Protocol (SOAP)

Masteroppgave i informasjons- og kommunikasjonsteknologi 2003 - Høgskolen i Agder, GrimstadIn SOAP, the entire XML object is generated on the server before it is returned to the client. This puts unnecessary strain on server systems in terms of both memory and CPU. The objectives are to find why SOAP does not allow streaming of responses, possible solutions to the problem and outline alternative transfer methods. Furthermore, compression techniques for a streaming SOAP environment are evaluated, as well as performance of streaming versus an alternative method of data retrieval. The feasibility study concluded that SOAP itself allows streaming of responses, but the HTTP binding does not. This binding specifies the issue of a HTTP fault code in case of a SOAP processing error, meaning the processing must be completed before a HTTP code can legally be issued. One alternative to streaming is using a Request/N-Response message pattern, and dividing the data over several responses. As HTTP only supports a Request/Response message pattern, implementing this is not possible. Either the HTTP binding must be rewritten to allow streaming of responses while processing a request or HTTP must be replaced with for example DIME as the transfer protocol for SOAP to overcome these problems. Tests are set up to find the most suitable compressor technique and to verify that streaming SOAP responses utilize server resources better then alternative transfer methods. Results show that bzip2 is the most suitable compressor technique. And that streaming utilizes memory considerably more efficient, especially with multiple clients connecting

On the performance of markup language compression

Data compression is used in our everyday life to improve computer interaction or simply for storage purposes. Lossless data compression refers to those techniques that are able to compress a file in such ways that the decompressed format is the replica of the original. These techniques, which differ from the lossy data compression, are necessary and heavily used in order to reduce resource usage and improve storage and transmission speeds. Prior research led to huge improvements in compression performance and efficiency for general purpose tools which are mainly based on statistical and dictionary encoding techniques. Extensible Markup Language (XML) is based on redundant data which is parsed as normal text by general-purpose compressors. Several tools for compressing XML data have been developed, resulting in improvements for compression size and speed using different compression techniques. These tools are mostly based on algorithms that rely on variable length encoding. XML Schema is a language used to define the structure and data types of an XML document. As a result of this, it provides XML compression tools additional information that can be used to improve compression efficiency. In addition, XML Schema is also used for validating XML data. For document compression there is a need to generate the schema dynamically for each XML file. This solution can be applied to improve the efficiency of XML compressors. This research investigates a dynamic approach to compress XML data using a hybrid compression tool. This model allows the compression of XML data using variable and fixed length encoding techniques when their best use cases are triggered. The aim of this research is to investigate the use of fixed length encoding techniques to support general-purpose XML compressors. The results demonstrate the possibility of improving on compression size when a fixed length encoder is used to compressed most XML data types

Conformance Checking and Simulation-based Evolutionary Optimization for Deployment and Reconfiguration of Software in the Cloud

Many SaaS providers nowadays want to leverage the cloud's capabilities also for their existing applications, for example, to enable sound scalability and cost-effectiveness. This thesis provides the approach CloudMIG that supports SaaS providers to migrate those applications to IaaS and PaaS-based cloud environments. CloudMIG consists of a step-by-step process and focuses on two core components. (1) Restrictions imposed by specific cloud environments (so-called cloud environment constraints (CECs)), such as a limited file system access or forbidden method calls, can be validated by an automatic conformance checking approach. (2) A cloud deployment option (CDO) determines which cloud environment, cloud resource types, deployment architecture, and runtime reconfiguration rules for exploiting a cloud's elasticity should be used. The implied performance and costs can differ in orders of magnitude. CDOs can be automatically optimized with the help of our simulation-based genetic algorithm CDOXplorer. Extensive lab experiments and an experiment in an industrial context show CloudMIG's applicability and the excellent performance of its two core components