High Performance Web Servers: A Study In Concurrent Programming Models

With the advent of commodity large-scale multi-core computers, the performance of software running on these computers has become a challenge to researchers and enterprise developers. While academic research and industrial products have moved in the direction of writing scalable and highly available services using distributed computing, single machine performance remains an active domain, one which is far from saturated. This thesis selects an archetypal software example and workload in this domain, and describes software characteristics affecting performance. The example is highly-parallel web-servers processing a static workload. Particularly, this work examines concurrent programming models in the context of high-performance web-servers across different architectures — threaded (Apache, Go and μKnot), event-driven (Nginx, μServer) and staged (WatPipe) — compared with two static workloads in two different domains. The two workloads are a Zipf distribution of file sizes representing a user session pulling an assortment of many small and a few large files, and a 50KB file representing chunked streaming of a large audio or video file. Significant effort is made to fairly compare eight web-servers by carefully tuning each via their adjustment parameters. Tuning plays a significant role in workload-specific performance. The two domains are no disk I/O (in-memory file set) and medium disk I/O. The domains are created by lowering the amount of RAM available to the web-server from 4GB to 2GB, forcing files to be evicted from the file-system cache. Both domains are also restricted to 4 CPUs. The primary goal of this thesis is to examine fundamental performance differences between threaded and event-driven concurrency models, with particular emphasis on user-level threading models. Additionally, a secondary goal of the work is to examine high-performance software under restricted hardware environments. Over-provisioned hardware environments can mask architectural and implementation shortcomings in software – the hypothesis in this work is that restricting resources stresses the application, bringing out important performance characteristics and properties. Experimental results for the given workload show that memory pressure is one of the most significant factors for the degradation of web-server performance, because it forces both the onset and amount of disk I/O. With an ever increasing need to support more content at faster rates, a web-server relies heavily on in-memory caching of files and related content. In fact, personal and small business web-servers are even run on minimal hardware, like the Raspberry Pi, with only 1GB of RAM and a small SD card for the file system. Therefore, understanding behaviour and performance in restricted contexts should be a normal aspect of testing a web server (and other software systems)

Exploration of Game Consoles as a legitimate computing platform for in-the-field biomedical data acquisition and management

Biomedical research increasingly requires for testings be conducted outside the lab, in the field such as the participant’s home or work environment. This type of research requires semi-autonomous computer systems that collect such data and send it back to the lab for processing and dissemination. A key aspect of this type of research is the selection of the required software and hardware components. These systems need to be reliable, allow considerable customizability and be readily accessible but also able to be locked down. In this paper we report a set of requirements for the hardware and software for such a system. We then utilise these requirements to evaluate the use of game consoles as a hardware platform in comparison to other hardware choices

Designing the Library of the Future

The University of Technology, Sydney (UTS) has embarked on a major redevelopment of its City Campus. A key element of this redevelopment is the planned construction of a new University Library at the centre of the redeveloped campus on the current site of Building 2, adjoining the UTS Tower, Building 1. This Library of the Future, which is planned to open for academic year 2015, will be a new kind of academic library which will aim to set a standard for the future. The focus of this report is on envisaging a Library of the Future, what it might be when it opens and how it might develop to retain its novelty so that it will continue to surprise and excite. To endeavour to imagine and create a Library of the Future is a daring and humbling enterprise: it must be designed to foster an effective academic community in the long term at UTS through its role as the knowledge hub of the University

Advanced Battery Technologies: New Applications and Management Systems

In recent years, lithium-ion batteries (LIBs) have been increasingly contributing to the development of novel engineering systems with energy storage requirements. LIBs are playing an essential role in our society, as they are being used in a wide variety of applications, ranging from consumer electronics, electric mobility, renewable energy storage, biomedical applications, or aerospace systems. Despite the remarkable achievements and applicability of LIBs, there are several features within this technology that require further research and improvements. In this book, a collection of 10 original research papers addresses some of those key features, including: battery testing methodologies, state of charge and state of health monitoring, and system-level power electronics applications. One key aspect to emphasize when it comes to this book is the multidisciplinary nature of the selected papers. The presented research was developed at university departments, institutes and organizations of different disciplines, including Electrical Engineering, Control Engineering, Computer Science or Material Science, to name a few examples. The overall result is a book that represents a coherent collection of multidisciplinary works within the prominent field of LIBs

Advanced user authentification for mobile devices

Access to the full-text thesis is no longer available at the author's request, due to 3rd party copyright restrictions. Access removed on 28.11.2016 by CS (TIS).Metadata merged with duplicate record ( http://hdl.handle.net/10026.1/1101 - now deleted) on 20.12.2016 by CS (TIS).Recent years have witnessed widespread adoption of mobile devices. Whereas initial popularity was driven by voice telephony services, capabilities are now broadening to allow an increasing range of data orientated services. Such services serve to extend the range of sensitive data accessible through such devices and will in turn increase the requirement for reliable authentication of users. This thesis considers the authentication requirements of mobile devices and proposes novel mechanisms to improve upon the current state of the art. The investigation begins with an examination of existing authentication techniques, and illustrates a wide range of drawbacks. A survey of end-users reveals that current methods are frequently misused and considered inconvenient, and that enhanced methods of security are consequently required. To this end, biometric approaches are identified as a potential means of overcoming the perceived constraints, offering an opportunity for security to be maintained beyond pointof- entry, in a continuous and transparent fashion. The research considers the applicability of different biometric approaches for mobile device implementation, and identifies keystroke analysis as a technique that can offer significant potential within mobile telephony. Experimental evaluations reveal the potential of the technique when applied to a Personal Identification Number (PIN), telephone number and text message, with best case equal error rates (EER) of 9%, 8% and 18% respectively. In spite of the success of keystroke analysis for many users, the results demonstrate the technique is not uniformly successful across the whole of a given population. Further investigation suggests that the same will be true for other biometrics, and therefore that no single authentication technique could be relied upon to account for all the users in all interaction scenarios. As such, a novel authentication architecture is specified, which is capable of utilising the particular hardware configurations and computational capabilities of devices to provide a robust, modular and composite authentication mechanism. The approach, known as IAMS (Intelligent Authentication Management System), is capable of utilising a broad range of biometric and secret knowledge based approaches to provide a continuous confidence measure in the identity of the user. With a high confidence, users are given immediate access to sensitive services and information, whereas with lower levels of confidence, restrictions can be placed upon access to sensitive services, until subsequent reassurance of a user's identity. The novel architecture is validated through a proof-of-concept prototype. A series of test scenarios are used to illustrate how IAMS would behave, given authorised and impostor authentication attempts. The results support the use of a composite authentication approach to enable the non-intrusive authentication of users on mobile devices.Orange Personal Communication Services Ltd

Classification of Aquifers

This dissertation contains three papers describing an approach to classifying aquifers and groundwater systems. The three papers bring together the development of a basin scale groundwater classification system that integrates the literature, data gathering, and data analysis and testing. The classification system is a comprehensive method designed to improve interdisciplinary communication and standardize how groundwater systems are compared in watersheds across in the west and potentially beyond. Aquifers and groundwater systems can be classified using a variety of independent methods to characterize geologic and hydraulic properties, the degree of connection with surface water, and geochemical conditions. In light of a growing global demand for water associated with population growth, land development, and the expected effects of climate change, a standardized approach for classifying groundwater systems at the watershed scale is needed. To this end, a comprehensive classification system is developed that combines recognized methods and new approaches into one system. The purpose of this approach is to provide groundwater professionals, policy makers, and watershed managers with a widely applicable classification system that reduces sometimes cumbersome complex groundwater databases and analyses to straightforward graphical representations. The proposed classification system uses basin geology, aquifer productivity, threats and impacts posed by humans, water quality, and the degree of groundwater/surface water exchange as classification criteria. The approach is based on literature values, reference databases, and basic hydrologic and hydrogeologic principles. The proposed classification system treats data set completeness as a variable and includes a tiered assessment protocol that depends on the quality and quantity of data. In addition, it assembles and catalogs groundwater information using a consistent set of nomenclature. It is designed to analyze and display results using Geographical Information System (GIS) mapping tools, while standardizing descriptions of groundwater conditions and to support resource managers as they make land use decisions at the watershed scale. Together, the three papers describe a method for comparing and contrasting aquifer properties and systems needed by watershed managers. It is argued that the proposed methodology is needed to assist managers and planner in understanding the role of aquifers in watersheds as well as for the broad multi-basin comparison of aquifer data . The classification method does not replace current standard practices traditionally used to assess or characterize aquifers and groundwater systems. However, it does provide a standard methodology by which existing and new hydrogeologic data can be organized, easily communicated, and broadly compared on a watershed scale of 1:100,000 to 1:250,000. It is believed this classification system will promote an improved technical understanding between groundwater professionals and natural resource managers. Three appendices are included in this dissertation. The appendices provide supporting information for the three papers and results for four case studies

Children’s Storytelling App For Detecting Potential Child Sexual Abuse

Child Sexual Abuse (CSA) is a global issue of concern warranting global mitigation strategies. This project designed a prototype storytelling app to foster uninhibited creative expression by children of their daily life events and associated feelings. By monitoring their children’s stories, parents and caregivers might be able to take supportive steps when stories reveal situations of potential CSA. Backed by a literature review and environmental scan, the prototype was designed through a participatory design process involving parents, caregivers and other adults concerned about CSA by way of a survey and focus groups. Participants were invited from Canada and India to examine cross-cultural notions around CSA and design elements. Research was conducted onsite in India for four months. Through further participatory steps, the prototype will be developed into an app that can be used by children both online and offline. The app will be hosted on a website to create a platform for parents to form a community of interest

Predicting the Future

Due to the increased capabilities of microprocessors and the advent of graphics processing units (GPUs) in recent decades, the use of machine learning methodologies has become popular in many fields of science and technology. This fact, together with the availability of large amounts of information, has meant that machine learning and Big Data have an important presence in the field of Energy. This Special Issue entitled “Predicting the Future—Big Data and Machine Learning” is focused on applications of machine learning methodologies in the field of energy. Topics include but are not limited to the following: big data architectures of power supply systems, energy-saving and efficiency models, environmental effects of energy consumption, prediction of occupational health and safety outcomes in the energy industry, price forecast prediction of raw materials, and energy management of smart buildings