On the Relation Between Mobile Encounters and Web Traffic Patterns: A Data-driven Study

Mobility and network traffic have been traditionally studied separately. Their interaction is vital for generations of future mobile services and effective caching, but has not been studied in depth with real-world big data. In this paper, we characterize mobility encounters and study the correlation between encounters and web traffic profiles using large-scale datasets (30TB in size) of WiFi and NetFlow traces. The analysis quantifies these correlations for the first time, across spatio-temporal dimensions, for device types grouped into on-the-go Flutes and sit-to-use Cellos. The results consistently show a clear relation between mobility encounters and traffic across different buildings over multiple days, with encountered pairs showing higher traffic similarity than non-encountered pairs, and long encounters being associated with the highest similarity. We also investigate the feasibility of learning encounters through web traffic profiles, with implications for dissemination protocols, and contact tracing. This provides a compelling case to integrate both mobility and web traffic dimensions in future models, not only at an individual level, but also at pairwise and collective levels. We have released samples of code and data used in this study on GitHub, to support reproducibility and encourage further research (https://github.com/BabakAp/encounter-traffic).Comment: Technical report with details for conference paper at MSWiM 2018, v3 adds GitHub lin

Greener and Smarter Phones for Future Cities: Characterizing the Impact of GPS Signal Strength on Power Consumption

Smart cities appear as the next stage of urbanization aiming to not only exploit physical and digital infrastructure for urban development but also the intellectual and social capital as its core ingredient for urbanization. Smart cities harness the power of data from sensors in order to understand and manage city systems. The most important of these sensing devices are smartphones as they provide the most important means to connect the smart city systems with its citizens, allowing personalization n and cocreation. The battery lifetime of smartphones is one of the most important parameters in achieving good user experience for the device. Therefore, the management and the optimization of handheld device applications in relation to their power consumption are an important area of research. This paper investigates the relationship between the energy consumption of a localization application and the strength of the global positioning system (GPS) signal. This is an important focus, because location-based applications are among the top power-hungry applications. We conduct experiments on two android location-based applications, one developed by us, and the other one, off the shelf. We use the results from the measurements of the two applications to derive a mathematical model that describes the power consumption in smartphones in terms of SNR and the time to first fix. The results from this study show that higher SNR values of GPS signals do consume less energy, while low GPS signals causing faster battery drain (38% as compared with 13%). To the best of our knowledge, this is the first study that provides a quantitative understanding of how the poor strength (SNR) of satellite signals will cause relatively higher power drain from a smartphone\u27s battery

Building up knowledge through passive WiFi probes

Inexpensive WiFi-capable hardware can be nowadays easily used to capture traffic from end users and extract knowledge. Such knowledge can be leveraged to support advanced services like user profiling, device classification. We review here the main building blocks to develop a system based on passive WiFi monitors, that is, cheap and viable sniffers which collect data from end devices even without an explicit association to any Wi-Fi network. We provide an overview of the services which can be enabled by such approach with three practical scenarios: user localization, user profiling and device classification. We evaluate the performance of each one of the three scenarios and highlight the challenges and threats for the aforementioned systems

Passive classification of Wi-Fi enabled devices

We propose a method for classifying Wi-Fi enabled mobile handheld devices (smartphones) and non-handheld devices (laptops) in a completely passive way, that is resorting neither to traffic probes on network edge devices nor to deep packet inspection techniques to read application layer information. Instead, classification is performed starting from probe requests Wi-Fi frames, which can be sniffed with inexpensive commercial hardware. We extract distinctive features from probe request frames (how many probe requests are transmitted by each device, how frequently, etc.) and take a machine learning approach, training four different classifiers to recognize the two types of devices. We compare the performance of the different classifiers and identify a solution based on a Random Decision Forest that correctly classify devices 95% of the times. The classification method is then used as a pre-processing stage to analyze network traffic traces from the wireless network of a university building, with interesting considerations on the way different types of devices uses the network (amount of data exchanged, duration of connections, etc.). The proposed methodology finds application in many scenarios related to Wi-Fi network management/optimization and Wi-Fi based services

The Role of Handheld Computers in Controlling Inter-Organizational Data Transactions

In spite of prior extensive research on the role of information systems (IS) in controlling interorganizational transactions, very little has been said about the role of handheld computers in inter-organizational control. The literature on handheld computers suggests that their facilities of mobility and connectivity engender usability patterns that are significantly different from those related to static and bulkier computers. Yet, the IS field lacks elaborate models explaining the role of handheld computers in inter-organizational control. This paper draws upon the philosophical assumptions of transactions costs theory to analyze this role. Four scenarios resulting from this analysis are appropriation and institutionalization of technology, and interaction and comprehension between the organizations. It further synthesizes these scenarios to propose four socio-technical systems of control that make electronic data transactions with handheld computers efficient. It argues that handheld computers supplant bureaucratic control, and engender more diverse and resilient systems of inter-organizational control. These roles will require IS researchers to rethink the sufficiency of traditional mechanisms of control suitable for efficient inter-organizational transactions, and induce the next wave of research on the control of electronic data transactions with inter-organizational IS

Empowerment of teaching and learning chemistry through information and communication technologies

There is an obvious growing of the importance of information and  communication technologies (ICTs) in science education. It is used as a tool for designing new learning environments, integrating virtual models and creating learning communities (e-learning). However, e-learning used in teaching and learning chemistry, including informative material in electronic forms such as; www-pages e-mails, and discussion forums enhances teaching and learning chemistry. In addition to the material delivery and implementation of new electronic tools the e-learning process requires support in technical matters, especial activation of learning processes, and cooperation between teachers to exchange their  experiences and ideas. It is very important to create e-learning in high quality that requires quality management to standardize approaches of e-learning. International cooperation would emphasize these requirements, and even more. In this paper I report experiences of developing a bilingual (English-Arabic) chemistry course in which web or virtual learning environment has been utilized. There is a need for increasing cooperation between teachers, in different countries web-based teaching and learning chemistry. Nowadays extremely actual and perspective educational  technique is used, which is the mobile learning (m-learning). Mobile  learning is the intersection of mobile computing (the application of small, portable, and wireless computing and communication devices) and e-learning (learning facilitated and supported through the use of  information and communications technology). Mobile learning that provides learning is truly independent of time and place and facilitated by portable computers capable of providing rich interactivity, total connectivity, and powerful processing. In May 2005, Ellen Wagner, senior director of GlobalEducation Solutions at Macromedia, proclaimed that the mobile revolution had finally arrived. [AJCE 4(3), Special Issue, May 2014

An end-to-end review of gaze estimation and its interactive applications on handheld mobile devices

In recent years we have witnessed an increasing number of interactive systems on handheld mobile devices which utilise gaze as a single or complementary interaction modality. This trend is driven by the enhanced computational power of these devices, higher resolution and capacity of their cameras, and improved gaze estimation accuracy obtained from advanced machine learning techniques, especially in deep learning. As the literature is fast progressing, there is a pressing need to review the state of the art, delineate the boundary, and identify the key research challenges and opportunities in gaze estimation and interaction. This paper aims to serve this purpose by presenting an end-to-end holistic view in this area, from gaze capturing sensors, to gaze estimation workflows, to deep learning techniques, and to gaze interactive applications.PostprintPeer reviewe

New Handheld Emissions Detector for Pinpointing the Location of Inadvertently Energized Objects in Urban Environments.

The power distribution infrastructure in the United States is deteriorating at a rapid rate exposing infrastructure wiring and creating potential shock hazards. Periodic road and sidewalk maintenance projects can also expose wiring and create energized objects. In urban settings inadvertently energized objects include: lamp posts, bus shelters, metal street curbs, sign posts, transformer vaults, and manhole covers as well as concrete and asphalt pavement. Every year electric shocks occur when people and domestic animals (such as dogs and cats) make incidental contact with these energized objects. In very rare cases the shocks from these contacts are lethal. Through current personal research, a new handheld detector was developed. It uses the emissions of an energized object to pinpoint the location and further analyzes the emissions to determine the likely cause of the shock hazard. This thesis focuses on advancing detection technology and creating a more capable, production-ready unit

Validity and reliability construct tests on the intensity scale of smartphone usage

This research aims to illustrate the intensity of smartphone usage in educational context, in order to analyze the validity and reliability construct of the intensity of smartphone usage and to determine the indicator of the intensity of smartphone usage. The data were collected using the intensity scale of smartphone usage. The intensity scale consisted of motivation, duration of activity, frequency of activity, presentation, direction of attitude, and interest. Smart PLS 3.0 program with reflective construct through 2nd Order CFA were also used to assist the research. The data comprised of 69 students of the Faculty of Psychology in University X Yogyakarta. The results show that the dimensions and indicators of the intensity of smartphone usage are valid and reliable. The most-dominant dimension reflecting the construction of the intensity of smartphone usage is the interest. The least-dominant dimension reflecting the construction of the intensity of smartphone usage is the motivation. Those things show that all the dimensions and indicators are able to reflect and form the intensity of smartphone usage. Thus, the measurement model can be accepted since the theory that illustrates the intensity of smartphone usage is in accordance with the empirical data obtained from the subject