A Preliminary Look into Unsolicited Mobile App Traffic

The number of smart devices keeps on growing every year, and with that the potential market for mobile apps. As of May 2016, Google Play hosted 2.6 million apps and had an accumulative total of 65 billion app downloads. Any developer can publish apps through Play, and it is quite prevalent to granting apps permission use the phone's network network interfaces at will and under very limited supervision (beyond overall traffic volume and bitwise access to an interface). This raises the following questions: can certain apps be harmful to users? Should we trust mobile developers to 'do no evil' in terms of the volume and type of traffic their apps generate? We are motivated to identify whether there is a need for more scrutiny on the connections apps make, especially when not in use

Llama : Towards Low Latency Live Adaptive Streaming

Multimedia streaming, including on-demand and live delivery of content, has become the largest service, in terms of traffic volume, delivered over the Internet. The ever-increasing demand has led to remarkable advancements in multimedia delivery technology over the past three decades, facilitated by the concurrent pursuit of efficient and quality encoding of digital media. Today, the most prominent technology for online multimedia delivery is HTTP Adaptive Streaming (HAS), which utilises the stateless HTTP architecture - allowing for scalable streaming sessions that can be delivered to millions of viewers around the world using Content Delivery Networks. In HAS, the content is encoded at multiple encoding bitrates, and fragmented into segments of equal duration. The client simply fetches the consecutive segments from the server, at the desired encoding bitrate determined by an ABR algorithm which measures the network conditions and adjusts the bitrate accordingly. This method introduces new challenges to live streaming, where the content is generated in real-time, as it suffers from high end-to-end latency when compared to traditional broadcast methods due to the required buffering at client. This thesis aims to investigate low latency live adaptive streaming, focusing on the reduction of the end-to-end latency. We investigate the impact of latency on the performance of ABR algorithms in low latency scenarios by developing a simulation model and testing prominent on-demand adaptation solutions. Additionally, we conduct extensive subjective testing to further investigate the impact of bitrate changes on the perceived Quality of Experience (QoE) by users. Based on these investigations, we design an ABR algorithm suitable for low latency scenarios which can operate with a small client buffer. We evaluate the proposed low latency adaption solution against on-demand ABR algorithms and the state-of-the-art low latency ABR algorithms, under realistic network conditions using a variety of client and latency settings

QoE Assessment for Multi-Video Object Based Media

Recent multimedia experiences using techniques such as DASH allow the streaming delivery to be adapted to suit network context. Object Based Media (OBM) provides even more flexibility as distinct media objects are streamed and combined based on user preferences, allowing the experience to be personalised for the user. As adaptation can lead to degradation, modelling and measuring Quality of Experience (QoE) are crucial to ensure a perceptibly-optimal user experience. QoE models proposed for DASH include quality-related factors from single video-object streams and hence, are unsuitable for multi-video OBM experiences. In this paper, we propose an objective method to quantify QoE for video-based OBM experiences. Our model provides different strategies to aggregate individual object QoE contributions for different OBM experience genres. We apply our model to a case study and contrast it with the QoE levels obtained using a standard QoE model for DASH

Improving quality of experience in adaptive low latency live streaming

HTTP Adaptive Streaming (HAS), the most prominent technology for streaming video over the Internet, suffers from high end-to-end latency when compared to conventional broadcast methods. This latency is caused by the content being delivered as segments rather than as a continuous stream, requiring the client to buffer significant amounts of data to provide resilience to variations in network throughput and enable continuous playout of content without stalling. The client uses an Adaptive Bitrate (ABR) algorithm to select the quality at which to request each segment to trade-off video quality with the avoidance of stalling to improve the Quality of Experience (QoE). The speed at which the ABR algorithm responds to changes in network conditions influences the amount of data that needs to be buffered, and hence to achieve low latency the ABR needs to respond quickly. Llama (Lyko et al. 28) is a new low latency ABR algorithm that we have previously proposed and assessed against four on-demand ABR algorithms. In this article, we report an evaluation of Llama that demonstrates its suitability for low latency streaming and compares its performance against three state-of-the-art low latency ABR algorithms across multiple QoE metrics and in various network scenarios. Additionally, we report an extensive subjective test to assess the impact of variations in video quality on QoE, where the variations are derived from ABR behaviour observed in the evaluation, using short segments and scenarios. We publish our subjective testing results in full and make our throughput traces available to the research community

Mechanism and biological role of Dnmt2 in Nucleic Acid Methylation

A group of homologous nucleic acid modification enzymes called Dnmt2, Trdmt1, Pmt1, DnmA, and Ehmet in different model organisms catalyze the transfer of a methyl group from the cofactor S-adenosyl-methionine (SAM) to the carbon-5 of cytosine residues. Originally considered as DNA MTases, these enzymes were shown to be tRNA methyltransferases about a decade ago. Between the presumed involvement in DNA modification-related epigenetics, and the recent foray into the RNA modification field, significant progress has characterized Dnmt2-related research. Here, we review this progress in its diverse facets including molecular evolution, structural biology, biochemistry, chemical biology, cell biology and epigenetics

Differential QoE in Picture-in-Picture Gaming Videos: A Subjective Study

Video streaming continues to be the largest service delivered on the internet. This includes gaming videos, delivered both on-demand and live, where gaming footage is usually accompanied by a video of the player overlaid on top of the gameplay -- resulting in Picture-In-Picture (PiP) content. Currently, PiP content is usually combined into a single video before being delivered to the client via technologies such as HTTP Adaptive Streaming (HAS). In this study, we investigated the QoE importance of gameplay and player elements in PiP gaming videos by varying the video quality of these elements individually. We conducted a subjective study, testing nine quality permutations based on three quality levels across three pieces of content from different gaming genres, with 30 participants recruited using an ethical crowdsourcing platform. We found that gameplay was significantly more important in terms of overall QoE, while the player element made a difference in only a few cases

Drop or Stop: Investigating the Impact of Playback Rate on QoE in Adaptive Video Streaming

Quality of Experience (QoE) is a crucial component of adaptive bitrate (ABR) streaming, with the effects of abrupt changes in playback quality or rebuffering, caused by delivery disruptions, being widely studied. However, the collective ABR community has a limited understanding of the effects of changes in playback rate on QoE. In this pioneering work, we investigate two aspects of playback rate fluctuations. In particular, we carry out two subjective studies to assess if a change in playback rate is more or less acceptable than a drop in video quality or a rebuffering event. Furthermore, we examine the effect of the transition in playback rate on QoE, comparing gradual and instant variations. Our subjective studies recruited 120 participants who evaluated 102 test sequences. In summary, we find that playback rate drops of 0.8-0.9 are imperceptible for most content, and rated similarly to a video quality drop to medium level. In contrast, lower playback rates of 0.6-0.7 were perceived as poorly as rebuffering events. Gradual changes in playback rate can offer better QoE, but only in limited cases depending on the content, target playback rate, as well as magnitude of change

Drop or Stop: Investigating the Impact of Playback Rate on QoE in Adaptive Video Streaming

No abstract available

QoE Assessment for Multi-Video Object Based Media

No abstract available