The Bits of Silence : Redundant Traffic in VoIP

Human conversation is characterized by brief pauses and so-called turn-taking behavior between the speakers. In the context of VoIP, this means that there are frequent periods where the microphone captures only background noise – or even silence whenever the microphone is muted. The bits transmitted from such silence periods introduce overhead in terms of data usage, energy consumption, and network infrastructure costs. In this paper, we contribute by shedding light on these costs for VoIP applications. We systematically measure the performance of six popular mobile VoIP applications with controlled human conversation and acoustic setup. Our analysis demonstrates that significant savings can indeed be achievable - with the best performing silence suppression technique being effective on 75% of silent pauses in the conversation in a quiet place. This results in 2-5 times data savings, and 50-90% lower energy consumption compared to the next better alternative. Even then, the effectiveness of silence suppression can be sensitive to the amount of background noise, underlying speech codec, and the device being used. The codec characteristics and performance do not depend on the network type. However, silence suppression makes VoIP traffic network friendly as much as VoLTE traffic. Our results provide new insights into VoIP performance and offer a motivation for further enhancements, such as performance-aware codec selection, that can significantly benefit a wide variety of voice assisted applications, as such intelligent home assistants and other speech codec enabled IoT devices.Peer reviewe

Mobility is the Message: Experiments with Mobile Media Sharing

This thesis explores new mobile media sharing applications by building, deploying, and studying their use. While we share media in many different ways both on the web and on mobile phones, there are few ways of sharing media with people physically near us. Studied were three designed and built systems: Push!Music, Columbus, and Portrait Catalog, as well as a fourth commercially available system – Foursquare. This thesis offers four contributions: First, it explores the design space of co-present media sharing of four test systems. Second, through user studies of these systems it reports on how these come to be used. Third, it explores new ways of conducting trials as the technical mobile landscape has changed. Last, we look at how the technical solutions demonstrate different lines of thinking from how similar solutions might look today. Through a Human-Computer Interaction methodology of design, build, and study, we look at systems through the eyes of embodied interaction and examine how the systems come to be in use. Using Goffman’s understanding of social order, we see how these mobile media sharing systems allow people to actively present themselves through these media. In turn, using McLuhan’s way of understanding media, we reflect on how these new systems enable a new type of medium distinct from the web centric media, and how this relates directly to mobility. While media sharing is something that takes place everywhere in western society, it is still tied to the way media is shared through computers. Although often mobile, they do not consider the mobile settings. The systems in this thesis treat mobility as an opportunity for design. It is still left to see how this mobile media sharing will come to present itself in people’s everyday life, and when it does, how we will come to understand it and how it will transform society as a medium distinct from those before. This thesis gives a glimpse at what this future will look like

Improving the Efficacy of Context-Aware Applications

In this dissertation, we explore methods for enhancing the context-awareness capabilities of modern computers, including mobile devices, tablets, wearables, and traditional computers. Advancements include proposed methods for fusing information from multiple logical sensors, localizing nearby objects using depth sensors, and building models to better understand the content of 2D images. First, we propose a system called Unagi, designed to incorporate multiple logical sensors into a single framework that allows context-aware application developers to easily test new ideas and create novel experiences. Unagi is responsible for collecting data, extracting features, and building personalized models for each individual user. We demonstrate the utility of the system with two applications: adaptive notification filtering and a network content prefetcher. We also thoroughly evaluate the system with respect to predictive accuracy, temporal delay, and power consumption. Next, we discuss a set of techniques that can be used to accurately determine the location of objects near a user in 3D space using a mobile device equipped with both depth and inertial sensors. Using a novel chaining approach, we are able to locate objects farther away than the standard range of the depth sensor without compromising localization accuracy. Empirical testing shows our method is capable of localizing objects 30m from the user with an error of less than 10cm. Finally, we demonstrate a set of techniques that allow a multi-layer perceptron (MLP) to learn resolution-invariant representations of 2D images, including the proposal of an MCMC-based technique to improve the selection of pixels for mini-batches used for training. We also show that a deep convolutional encoder could be trained to output a resolution-independent representation in constant time, and we discuss several potential applications of this research, including image resampling, image compression, and security

In situ underwater microwave oil spill and oil slick thickness sensor

Nearly 30 percent of oil drilled globally is done offshore. Oil spillage offshore have far-reaching consequences on the environment, aquatic lives, and livelihoods as it was evident in the numerous accidents such as the Deepwater Horizon and Bonga oil spillages. Apart from detecting oil spillages, the determination of the oil slick thickness is very important. This is to enable the estimation of the volume and spread of oil discharged in oceans, seas and lakes. This information could guide the oil spill countermeasures and provide the basis for legal actions against the defaulting parties. The viability of the use of radar in the detection of oil spill has already been established by airborne and space borne synthetic aperture radar (SAR). Notwithstanding, the high latency associated with SARs and its susceptibility of false positive and false negative detection of oil slick makes it vulnerable. It has also not been very successful in the determination of oil slick thickness. In situ methods such as the capacitive, conductive and optical based approaches have been used to detect as well as determine oil slick thickness. Some of these contact-based approaches are susceptible to corrosion, fouling and require several calibrations. Radio frequency (RF) signals in seawater suffer from attenuation and dispersion due to the high conductivity of the medium. Antennas, ideally matched to free space, suffer impedance mismatches when immersed in seawater. In this thesis, we proposed the novel approach of using microwave techniques to detect oil spillage and determine oil slick thickness based on a contact-based in situ approach. The work began by undertaking an investigation into the properties of the North Sea water which was used as the primary transmission medium for the study. Subsequently, the research developed an ultrawideband antenna that radiated underwater, which was encapsulated in polydimethylsiloxane (PDMS). The antenna-sensor with a Faraday cage was used to develop a novel microwave oil spill sensor. A communication backbone was designed for the sensor using long range (LoRa) 868 MHz frequency based on a bespoke braid antenna buffered by oil impregnated papers to ameliorate against the influence of the seawater surface. Using a four layered RF switch controller and an antenna array consisting of four antenna-sensors, a novel microwave oil slick thickness sensor was developed. The antenna-sensors were arranged in a cuboid fashion with antenna-sensor 3 and antenna-sensor 4 capable of detecting oil slick thickness at 23 mm and 46 mm using their transmission coefficient (S43) of -10 dB and -19 dB compared to that of the pure seawater respectively. For the 69 mm and 92 mm thickness, the transmission coefficient (S21) of antenna-sensor 1 and antenna-sensor 2 was used to determine these thicknesses with values of -13.5 dB and -24.14 dB with respect to that of pure seawater