Advanced Web User Monitoring with Real-Time Communications Devices

This paper presents a new approach to web user monitoring with real-time communications devices. Proposed solution is based on a combination of WebRTC technology, performance data logging and third party services. This solutions allows measurement of a user’s web performance data, evaluated user’s behavior and makes gender and age classification. The results are an important tool in understanding what people think and feel while browsing a website. Thanks to this expertise we can better tailor web page content to achieve our business goals. Experimental results published in this paper were conducted on real data and show that the proposed solution of capturing and transforming face images from a video stream allows achievement of very high accuracy of gender and age classification by third party services

Process Mining IPTV Customer Eye Gaze Movement Using Discrete-time Markov Chains

Human-Computer Interaction (HCI) research has extensively employed eye-tracking technologies in a variety of fields. Meanwhile, the ongoing development of Internet Protocol TV (IPTV) has significantly enriched the TV customer experience, which is of great interest to researchers across academia and industry. A previous study was carried out at the BT Ireland Innovation Centre (BTIIC), where an eye tracker was employed to record user interactions with a Video-on-Demand (VoD) application, the BT Player. This paper is a complementary and subsequent study of the analysis of eye-tracking data in our previously published introductory paper. Here, we propose a method for integrating layout information from the BT Player with mining the process of customer eye movement on the screen, thereby generating HCI and Industry-relevant insights regarding user experience. We incorporate a popular Machine Learning model, a discrete-time Markov Chain (DTMC), into our methodology, as the eye tracker records each gaze movement at a particular frequency, which is a good example of discrete-time sequences. The Markov Model is found suitable for our study, and it helps to reveal characteristics of the gaze movement as well as the user interface (UI) design on the VoD application by interpreting transition matrices, first passage time, proposed ‘most likely trajectory’ and other Markov properties of the model. Additionally, the study has revealed numerous promising areas for future research. And the code involved in this study is open access on GitHub

User-activity aware strategies for mobile information access

Information access suffers tremendously in wireless networks because of the low correlation between content transferred across low-bandwidth wireless links and actual data used to serve user requests. As a result, conventional content access mechanisms face such problems as unnecessary bandwidth consumption and large response times, and users experience significant performance degradation. In this dissertation, we analyze the cause of those problems and find that the major reason for inefficient information access in wireless networks is the absence of any user-activity awareness in current mechanisms. To solve these problems, we propose three user-activity aware strategies for mobile information access. Through simulations and implementations, we show that our strategies can outperform conventional information access schemes in terms of bandwidth consumption and user-perceived response times.Ph.D.Committee Chair: Raghupathy Sivakumar; Committee Member: Chuanyi Ji; Committee Member: George Riley; Committee Member: Magnus Egerstedt; Committee Member: Umakishore Ramachandra

Improving Mobile Network Performance Through Measurement-driven System Design Approaches

Mobile networks are complex, dynamic, and often perform poorly. Many factors affect network performance and energy consumption: examples include highly varying network latencies and loss rates, diurnal user movement patterns in cellular networks that impact network congestion, and how radio energy states interacts with application traffic. Because mobile devices experience uniquely dynamic and complex network conditions and resource tradeoffs, incorporating ongoing, continuous measurements of network performance, resource usage and user and app behavior into mobile systems is essential in addressing the pervasive performance problems in these systems. This dissertation examines five different approaches to this problem. First, we discuss three measurement studies which help us understand mobile systems and how to improve them. The first examines how RRC state performance impacts network performance in the wild and argues carriers should measure RRC state performance from the user's perspective when managing their networks. The second looks at trends in applications' background network energy consumption, and shows that more systematic approaches are needed to manage app behavior. The third examines how Server Push, a new feature of HTTP/2, can in certain cases improve mobile performance, but shows that it is necessary to use measurements to determine if Server Push will be helpful or harmful. Two other projects show how measurements can be incorporated directly into systems that predict and manage network traffic. One project examines how a carrier can support prefetching over time spans of hours by predicting the network loads a user will see in the future and scheduling highly delay-tolerant traffic accordingly. The other examines how the network requests of mobile apps can be predicted, a first step towards an automated and general app prefetching system. Overall, measurements of network performance and app and user behavior are powerful tools in building better mobile systems.PHDComputer Science & EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/136944/1/sanae_1.pd

Enhancing curriculum design and delivery with OER

This paper reports on the key findings from the EVOL-OER project which aims to develop a deeper understanding of the reuse of open educational resources (OERs) by academics in Higher Education Institutions (HEIs). This paper builds on the JISC OER Impact study by exploring and expanding on the Ratified quadrant of the study’s landscape of reuse framework (White & Manton, 2011). This paper puts forward a different four-quadrant diagram called ‘OER-enhanced curriculum’ to illustrate different approaches adopted by academics to embedding OER into curriculum design and delivery. Key issues in relation to motivation and challenges in reusing OER are discussed

ROVER: a DNS-based method to detect and prevent IP hijacks

2013 Fall.Includes bibliographical references.The Border Gateway Protocol (BGP) is critical to the global internet infrastructure. Unfortunately BGP routing was designed with limited regard for security. As a result, IP route hijacking has been observed for more than 16 years. Well known incidents include a 2008 hijack of YouTube, loss of connectivity for Australia in February 2012, and an event that partially crippled Google in November 2012. Concern has been escalating as critical national infrastructure is reliant on a secure foundation for the Internet. Disruptions to military, banking, utilities, industry, and commerce can be catastrophic. In this dissertation we propose ROVER (Route Origin VERification System), a novel and practical solution for detecting and preventing origin and sub-prefix hijacks. ROVER exploits the reverse DNS for storing route origin data and provides a fail-safe, best effort approach to authentication. This approach can be used with a variety of operational models including fully dynamic in-line BGP filtering, periodically updated authenticated route filters, and real-time notifications for network operators. Our thesis is that ROVER systems can be deployed by a small number of institutions in an incremental fashion and still effectively thwart origin and sub-prefix IP hijacking despite non-participation by the majority of Autonomous System owners. We then present research results supporting this statement. We evaluate the effectiveness of ROVER using simulations on an Internet scale topology as well as with tests on real operational systems. Analyses include a study of IP hijack propagation patterns, effectiveness of various deployment models, critical mass requirements, and an examination of ROVER resilience and scalability