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

Data literacy in the smart university approach

Equipping classrooms with inexpensive sensors for data collection can provide students and teachers with the opportunity to interact with the classroom in a smart way. In this paper two approaches to acquiring contextual data from a classroom environment are presented. We further present our approach to analysing the collected room usage data on site, using low cost single board computer, such as a Raspberry Pi and Arduino units, performing a significant part of the data analysis on-site. We demonstrate how the usage data was used to model specifcic room usage situation as cases in a Case-based reasoning (CBR) system. The room usage data was then integrated in a room recommender system, reasoning on the formalised usage data, allowing for a convenient and intuitive end user experience based on the collected raw sensor data. Having implemented and tested our approaches we are currently investigating the possibility of using (XML)Schema-informed compression to enhance the security and efficiency of the transmission of a large number of sensor reports generated by interpreting the raw data on-site, to our central data sink. We are investigating this new approach to usage data transmission as we are aiming to integrate our on-going work into our vision of the Smart University to ensure and enhance the Smart University's data literacy

Practice makes perfect – gamification of a competitive learning experience

The ability to provide and implement software solutions is a fundamental component of a computer scientist curriculum. Commonly referred to as the ability to program, this task involves the development of programs to address everyday problems. Over the last decade teaching practices have evolved alongside programming languages to facilitate the learning process. While abstracting the level of understanding has helped students with the fundamentals of software development, issues related to students’ engagement and motivation are still not adequately addressed. With motivation being a vital component of the students’ life cycle and at the basis of their engagement, the concept of software engineering introduced in the class needs to be revised and become more engaging so as to be practised thoroughly by the students. To address these challenges, educators have devised numerous frameworks to allow students to hone their programming skills. The idea of embedding gaming aspects into the learning cycle has led to the development of techniques such as serious games and game-based learning, while more recent techniques have been unified under the term gamification. Several researchers have incorporated the gamification concept into computer science classes in order to improve students’ engagement with the teaching material, with early evaluations confirming the effectiveness of this approach. The present study focuses on the use of a gamification platform to create stimulating content and increase motivation. Students were presented with a new gamification system designed to attract and hold their attention through a number of programming challenges in the form of a contest. The results of the experiment demonstrate the students’ behavioural changes towards a deeper cognitive engagement. The paper then further discusses the challenges that have arisen in this new learning environment, such as demotivation of students with low contest rankings. Teaching how to write good software has been part of an ongoing debate for the last decade. With student motivation being a central component, this paper discusses the use of a gamification environment to engage students with the teaching material and reinforce the concepts of software engineering introduced in class

The application of domain-specific languages within distributed computing

During the last decade scientists have developed earthquake early warning systems EEWS with the intent of alerting citizens of seismic events. The technology is based on the fact that warning signals travels faster than seismic waves. Current EEWS however rely on expensive equipment which are not feasible to deploy in developing countries. This project describes the development of a system based on a more open and low-cost solution. In this scenario the project will focus on the application of Domain-specific languages DSLs to orchestrate different aspects of the system. The DSL will be used to filter, store and share data over the network as well improve the functionality. This will enhance the software to allow an easier understanding of the domain problem and therefore making it faster to write, debug and maintain

XML-compression techniques for efficient network management

XML has become a standard widely used in wireless networking technologies to improve flexibility and interoperability between heterogeneous applications. However, applying this technology to areas such as network management across a wireless embedded internet can pose significant challenges due to the verbosity of XML. A number of compression techniques and tools have been applied to this problem to help transform highly-structured data into a more compact form. Despite this choice, there is a lack of support for tools which are optimised for embedded computing. In this paper we will show the performance trade-offs that exist when compression is applied using different techniques. Furthermore, we will describe a tool which has been specially designed to be used within the domain of network management within a constrained environment

Towards a real-time data sharing system for mobile devices

Mobile devices are increasingly used for information sharing. The sensors embedded inside these devices are generating a range of information about their location, surrounding environment and user activities. This information can be shared with others in real-time so that it can be used or analysed instantaneously. The popularity of participatory sensing involving humans and mobile devices(phones, PDAs, tablets etc) has also fuelled the growth of large scale data management. Although the typical network bandwidth available in mobile devices has been improving it remains limited with the rise in communication activity. Therefore, data could be optimised on the device to make it more suitable for the available network bandwidth. A scalable real-time data sharing system can be built by using existing message formats, messaging architectures and compression techniques. We will look at the bandwidth limitation and scalability issue with special focus on the impact of message compression in such networks

Teaching networking fundamentals with sound

There have been significant levels of research into how to use technology to teach programming principles. However, there has been less research to show how technology can be used to help teach network fundamentals in a creative way. Instead, simulation has been widely adopted as the main software tool when teaching networking concepts. In this paper we examine a more applied approach to help students gain some knowledge of fundamental concepts in networking such as bandwidth, throughput and latency. We achieved this by designing a tool to support the transmission of data over sound and examined its use on a group (n=20) of networking students

Towards markup-aware text compression

Although text compression can be successfully applied to markup languages, it does so without any semantic knowledge of the data types present within the markup. In this paper we illustrate how this added knowledge can be used to develop a hybrid tool which combines traditional text compression with markup-awareness to improve compression size against existing well known text compression tools. Our results show that for highly structured markup it is possible to improve the level of compression by around 20% compared to the best performing existing tool we studied. We describe the limitations of our approach and discuss potential implementation options with the overall goal being to produce a practical Unix-like tool