The Optimization of XML Data Transfer Through Hybrid Compression Standardizatio

With the dawn of the information age upon us, the ability to efficiently transfer and analyze data continues to be a paramount topic that must be addressed to sustain the continued growth of modern computing systems. One of the most widely used standards for communication between distributed systems is Extensible Markup Language (XML). XML has several advantages to other formats but the size of the data can become large do to the verbose nature of the metadata included in the XML structure. This increased size can significantly impact data transfer rates and processing time required to search the information contained within. This research employs a Design Science research methodology to demonstrate that compressing portions of the XML data and generating keyword searchable fields can significantly improve the time required to transfer and process XML data. Through the combined use of Design of Experiment principles, a software artifact and a distributed computing environment, a quantitative analysis was performed to demonstrate the performance improvements that can be gained through the use of a hybrid compression approach. By using this hybrid approach portions of the XML data can be compressed while other portions remain decompressed to ensure the data can still be quickly searched and the data can be interpreted by humans which was one of the significant features that led to XML's gain in popularity. The research concludes with several recommendations that could be incorporated into existing XML standards to improve the integration of compressed data elements in XML documents without the need to pre-define an XML schema.