Optimise web browsing on heterogeneous mobile platforms:a machine learning based approach

Web browsing is an activity that billions of mobile users perform on a daily basis. Battery life is a primary concern to many mobile users who often find their phone has died at most inconvenient times. The heterogeneous mobile architecture is a solution for energy-efficient mobile web browsing. However, the current mobile web browsers rely on the operating system to exploit the underlying architecture, which has no knowledge of the individual web workload and often leads to poor energy efficiency. This paper describes an automatic approach to render mobile web workloads for performance and energy efficiency. It achieves this by developing a machine learning based approach to predict which processor to use to run the web browser rendering engine and at what frequencies the processor cores of the system should operate. Our predictor learns offline from a set of training web workloads. The built predictor is then integrated into the browser to predict the optimal processor configuration at runtime, taking into account the web workload characteristics and the optimisation goal: whether it is load time, energy consumption or a trade-off between them. We evaluate our approach on a representative ARM big.LITTLE mobile architecture using the hottest 500 webpages. Our approach achieves 80% of the performance delivered by an ideal predictor. We obtain, on average, 45%, 63.5% and 81% improvement respectively for load time, energy consumption and the energy delay product, when compared to the Linux governo

Energy-efficient mobile Web computing

Next-generation Web services will be primarily accessed through mobile devices. However, mobile devices are low-performance and stringently energy-constrained. In my dissertation, I propose the design of a high-performance and energy-efficient mobile Web computing substrate. It is a hardware/software co-designed system that delivers satisfactory user quality-of-service (QoS) experience on a mobile energy budget. The key insight is that the traditional interfaces between different Web stacks need to be enhanced with new abstractions that express user QoS experience and that expose architectural-level complexities. On the basis of the enhanced interfaces, I propose synergistic cross-layer optimizations across the processor architecture, Web runtime, programming language, and application layers to maximize the whole system efficiency. The contributions made in this dissertation will likely have a long-term impact because the target application domain, the Web, is becoming a universal mobile development platform, and because our solutions target the fundamental computation layers of the Web domain.Electrical and Computer Engineerin

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

Design and implementation of a traffic control framework in Firefox OS

Today's smartphones include a rich feature-set as well as various wireless interfaces that provide extra services rather than just voice communication or messaging, as it occurred with traditional mobile phones. Additionally, the widespread use of mobile devices using Third Generation (3G) and Long Term Evolution (LTE) networks has led to the development of various applications (apps) that take advantage of the always-on Internet connectivity provided by these networks (e.g. instant messaging and social network services). Unlike traditional Internet apps (e.g. web surfing and file transfer), the emerging apps that rely on always-on connectivity are often constantly running in the background to receive messages and status updates. This behavior causes that apps continuously generate short app signaling messages such as keep-alive and ping requests to maintain the always-on connectivity. Although the traffic volume of keep-alive messages is not large, frequent short messages can incur a large amount of related signaling traffic in the mobile network. In 3G or LTE networks, the User Equipment (UE) and the Radio Access Network (RAN) keep the Radio Resource Control (RRC) states. The UE stays in Connected mode when it transmits or receives data during active periods and stays in Idle mode during inactive periods. To send even a small data packet, the UE changes the state to the Connected mode prior to transmission. This radio state change generates a lot of network signaling messages, resulting in a rapid increase in traffic loading. Large amounts of network signaling traffic leads to two major problems: rapid drainage of the mobile device's battery and a signaling traffic surge in the mobile network. Since the air interface is a spare resource and the traffic for mobile end devices will grow enormously, it is important that the wireless resources are used in the most efficient way. However, this is not true for current networks as there is not alignment between devices, apps and the network.This document proposes a traffic control framework which acts as an interface between the apps and the network and allows the network operator to aggregate packets prior to transmission. The aggregated packets are sent out at once after a configurable amount of time which means for instance that resources on the wireless link have to be reserved only once for a number of app signaling packets and not for each packet separately. By this the packet transmission will be bursty which will improve network efficiency as the amount of signaling messages is minimized. In addition, battery runtime is improved as lower signaling overhead will reduce the activity time and energy consumption within devices.Hoy en día los smartphones incorporan un amplio conjunto de utilidades, así como varias interfaces inalámbricas que proporcionan servicios adicionales a los ofrecidos por los teléfonos móviles convencionales. Por otra parte, el uso generalizado de las redes 3G y LTE ha originado el desarrollo de numerosas aplicaciones que aprovechan las ventajas que ofrecen dichas redes, un ejemplo son las aplicaciones de redes sociales. Estas aplicaciones, a diferencia de otras como la navegación web o la descarga de archivos, están constantemente ejecutándose en segundo plano y recibiendo notificaciones de actualización de estado. Este comportamiento propicia el intercambio de pequeños mensajes de señalización para mantener la conexión, tales como mensajes "keep alive" o "ping requests". A pesar de que el volumen de estos mensajes no es elevado, su constante intercambio puede ocasionar una gran cantidad de tráfico de señalización en la red. En las redes 3G o LTE, el equipo de usuario (UE) y la red de acceso radio terrestre (RAN) mantienen los estados RRC. El equipo de usuario permanece en el estado activo cuando transmite o recibe datos y retorna al estado de reposo durante los periodos inactivos. El envío de un pequeño paquete de datos supone la transición desde el estado de reposo al estado activo. Este comportamiento genera muchos mensajes de señalización e implica un rápido incremento en el tráfico de la red. Este incremento del tráfico de señalización ocasiona dos grandes problemas: la sobrecarga de la red y un impacto negativo en el consumo de batería de los dispositivos móviles. Es de vital importancia que se haga un uso eficiente de los recursos de red, ya que el aire, en este caso el canal de comunicación, es un medio compartido. Además, se espera que el tráfico generado por los dispositivos móviles crezca enormemente en los próximos años. Las redes móviles actuales no son utilizadas de un modo eficiente debido a la falta de interacción entre la red, los dispositivos móviles y las aplicaciones. Este documento presenta una plataforma de control de tr a co que actúa como interfaz entre las aplicaciones y la red, permitiendo al operador de red agregar los paquetes antes de su transmisión. Esto permite, por ejemplo, que los recursos de red sean reservados s olo una vez para la ráfaga de paquetes y no para cada paquete individualmente, lo cual minimiza la cantidad de mensajes de señalización. Esta propuesta no sólo ayuda a mejorar la eficiencia de la red, sino que además optimiza el uso de la batería, ya que una disminución del tráfico de señalización provoca una reducción del tiempo de actividad y consumo de energía de los dispositivos móviles.Ingeniería Telemátic