Cloud-based or On-device: An Empirical Study of Mobile Deep Inference

Modern mobile applications are benefiting significantly from the advancement in deep learning, e.g., implementing real-time image recognition and conversational system. Given a trained deep learning model, applications usually need to perform a series of matrix operations based on the input data, in order to infer possible output values. Because of computational complexity and size constraints, these trained models are often hosted in the cloud. To utilize these cloud-based models, mobile apps will have to send input data over the network. While cloud-based deep learning can provide reasonable response time for mobile apps, it restricts the use case scenarios, e.g. mobile apps need to have network access. With mobile specific deep learning optimizations, it is now possible to employ on-device inference. However, because mobile hardware, such as GPU and memory size, can be very limited when compared to its desktop counterpart, it is important to understand the feasibility of this new on-device deep learning inference architecture. In this paper, we empirically evaluate the inference performance of three Convolutional Neural Networks (CNNs) using a benchmark Android application we developed. Our measurement and analysis suggest that on-device inference can cost up to two orders of magnitude greater response time and energy when compared to cloud-based inference, and that loading model and computing probability are two performance bottlenecks for on-device deep inferences.Comment: Accepted at The IEEE International Conference on Cloud Engineering (IC2E) conference 201

A Survey of Performance Optimization for Mobile Applications

Nowadays there is a mobile application for almost everything a user may think of, ranging from paying bills and gathering information to playing games and watching movies. In order to ensure user satisfaction and success of applications, it is important to provide high performant applications. This is particularly important for resource constraint systems such as mobile devices. Thereby, non-functional performance characteristics, such as energy and memory consumption, play an important role for user satisfaction. This paper provides a comprehensive survey of non-functional performance optimization for Android applications. We collected 155 unique publications, published between 2008 and 2020, that focus on the optimization of non-functional performance of mobile applications. We target our search at four performance characteristics, in particular: responsiveness, launch time, memory and energy consumption. For each performance characteristic, we categorize optimization approaches based on the method used in the corresponding publications. Furthermore, we identify research gaps in the literature for future work

Acoustic Sensing: Mobile Applications and Frameworks

Acoustic sensing has attracted significant attention from both academia and industry due to its ubiquity. Since smartphones and many IoT devices are already equipped with microphones and speakers, it requires nearly zero additional deployment cost. Acoustic sensing is also versatile. For example, it can detect obstacles for distracted pedestrians (BumpAlert), remember indoor locations through recorded echoes (EchoTag), and also understand the touch force applied to mobile devices (ForcePhone). In this dissertation, we first propose three acoustic sensing applications, BumpAlert, EchoTag, and ForcePhone, and then introduce a cross-platform sensing framework called LibAS. LibAS is designed to facilitate the development of acoustic sensing applications. For example, LibAS can let developers prototype and validate their sensing ideas and apps on commercial devices without the detailed knowledge of platform-dependent programming. LibAS is shown to require less than 30 lines of code in Matlab to implement the prototype of ForcePhone on Android/iOS/Tizen/Linux devices.PHDComputer Science & EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/143971/1/yctung_1.pd

Systems and Methods for Measuring and Improving End-User Application Performance on Mobile Devices

In today's rapidly growing smartphone society, the time users are spending on their smartphones is continuing to grow and mobile applications are becoming the primary medium for providing services and content to users. With such fast paced growth in smart-phone usage, cellular carriers and internet service providers continuously upgrade their infrastructure to the latest technologies and expand their capacities to improve the performance and reliability of their network and to satisfy exploding user demand for mobile data. On the other side of the spectrum, content providers and e-commerce companies adopt the latest protocols and techniques to provide smooth and feature-rich user experiences on their applications. To ensure a good quality of experience, monitoring how applications perform on users' devices is necessary. Often, network and content providers lack such visibility into the end-user application performance. In this dissertation, we demonstrate that having visibility into the end-user perceived performance, through system design for efficient and coordinated active and passive measurements of end-user application and network performance, is crucial for detecting, diagnosing, and addressing performance problems on mobile devices. My dissertation consists of three projects to support this statement. First, to provide such continuous monitoring on smartphones with constrained resources that operate in such a highly dynamic mobile environment, we devise efficient, adaptive, and coordinated systems, as a platform, for active and passive measurements of end-user performance. Second, using this platform and other passive data collection techniques, we conduct an in-depth user trial of mobile multipath to understand how Multipath TCP (MPTCP) performs in practice. Our measurement study reveals several limitations of MPTCP. Based on the insights gained from our measurement study, we propose two different schemes to address the identified limitations of MPTCP. Last, we show how to provide visibility into the end- user application performance for internet providers and in particular home WiFi routers by passively monitoring users' traffic and utilizing per-app models mapping various network quality of service (QoS) metrics to the application performance.PHDComputer Science & EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/146014/1/ashnik_1.pd

Skin Portraiture: Embodied Representations in Contemporary Art

In recent years, human skin has been explored as a medium, metaphor, and milieu. Images of and objects made from skin flesh out the critical role it plays in experiences of embodiment such as reflexivity, empathy, and relationality, expanding conceptions of difference. This project problematizes the correlation between the appearance of the epidermis and a person’s identity. By depicting the subject as magnified, fragmented, anatomized patches of skin, “skin portraiture”—a sub-genre of portraiture I have coined—questions what a portrait is and what it can achieve in contemporary art. By circumnavigating and obfuscating the subject’s face, skin portraiture perforates the boundaries and collapses the distance between bodies. Feminist, this project pays attention to skin portraits made by women. To better understand skin, each chapter is focused on a particular skin metaphor. In the preface, a consideration of skin and its representation leads into an investigation of the skin-as-self metaphor in the introduction (chapter one). Framing the skin as an organ we dwell in, the skin-as-home metaphor (chapter two) explores touch and its role in experiences of empathy. Turning to the idea that skin is a garment, the skin-as-clothing metaphor (chapter three) fleshes out relationality and a queering of skin. Tackling race and skin colour, the skin-as-screen metaphor (chapter four) investigates the embodied experiences of mixed-raced, multicultural women. Addressing a loss of difference at the level of skin within bioengineering, the skin-as-technology metaphor (chapter five) considers the collapse of differences between bodies and species within bio-art

EURAU18 Alicante: Retroactive Research: Congress Proceedings

An interdisciplinary research of architecture is something that society demands from our profession. Furthermore, in many countries that are currently immersed in a recessive economic process, it is the only possible solution. In that context, it is urgent to clarify the scope of our projects: Those whose ultimate goal consists of going beyond the limits of other disciplines through the application of architecture. Starting with Architecture’s capacity to learn from other disciplines and to follow their guidelines and techniques, we will build and offer new specific tools. With these new tools, our research will provide the opportunity to challenge and expand the boundaries of those original disciplines. Traditionally, architecture supported itself by various branches of knowledge to advance its proposals: Economic Changes Social organizations Environmental Crisis and Natural Catastrophes Structural Knowledge Artistic Trends New Materials Technological Advances Political positions and Conflicts. While the resulting architectures are excellent examples of applying these areas of knowledge, our interest lies in the reverse process: how the discipline of architecture can cause changes in others. It is an applied research that extends its scope to a prior discourse that originated in the past. That is to say, becomes a Retroactive Research. In the end, the architectural project is an effective document that not only establishes a program but also defines the author as an entrepreneur, understanding this quality as a position that opens the door to different types of practices that architects can exercise: from running a professional architecture office, to teach, to do interior and furniture design, to write, to design digital scenarios, to work in social associations, to collaborate with research centres

Human-Machine Communication: Complete Volume. Volume 6

his is the complete volume of HMC Volume 6