Felix Xiaozhu Lin

Why are web browsers slow on smartphones

We report the first work that examines the internals of web browsers on smartphones, using the WebKit codebase, two generations of Android smartphones, and webpages visited by 25 smart-phone users over three months. We make many surprising findings. First, over half of the webpages visited by smartphone users are not optimized for mobile devices. This highlights the importance of client-based optimization and the limitation of prior work that only studies mobile webpages. Second, while prior work suggests that several compute-intensive operations should be the focus of optimization, our measurement and analysis show that their improvement will only lead to marginal performance gain with existing webpages. Furthermore, we find that resource loading, ignored by all except one prior work, contributes most to the browser delay. While our results agree with a recent network study showing that network round-trip time is a major problem, we further demonstrate how the internals of the browser and operating system contribute to the browser delay and therefore reveal new opportunities for optimization.

How far can client-only solutions go for mobile browser speed?

Mobile browser is known to be slow because of the bottleneck in resource loading. Client-only solutions to improve resource loading are attractive because they are immediately deployable, scalable, and secure. We present the first publicly known treatment of client-only solutions to understand how much they can improve mobile browser speed without infrastructure support. Leveraging an unprecedented set of web usage data collected from 24 iPhone users continuously over one year, we examine the three fundamental, orthogonal approaches a client-only solution can take: caching, prefetching, and speculative loading. Speculative loading, as is firstly proposed and studied in this work, predicts and speculatively loads the subresources needed to open a webpage once its URL is given. We show that while caching and prefetching are highly limited for mobile browsing, speculative loading can be significantly more effective. Empirically, we show that client-only solutions can improve the browser speed by about 1.4 second on average for websites visited by the 24 iPhone users. We also report the design, realization, and evaluation of speculative loading in a WebKit-based browser called Tempo. On average, Tempo can reduce browser delay by 1 second (~20%).

Draining our glass: an energy and heat characterization of Google Glass

The Google Glass is a mobile device designed to be worn as eyeglasses. This form factor enables new use cases, such as hands-free video chat and web search. However, its shape also hampers its potential: (1) battery size, and therefore lifetime, is limited by a need for the device to be lightweight, and (2) high-power processing leads to significant heat, which should be limited due to the compact form factor and proximity to the users skin. We use an Explorer Edition of Glass (XE12) to study the power and thermal characteristics of optical head-mounted display devices. We share insights and implications to limit power draw to increase the safety and utility of head-mounted devices.

Reflex: using low-power processors in smartphones without knowing them

To accomplish frequent, simple tasks with high efficiency, it is necessary to leverage low-power, microcontroller-like processors that are increasingly available on mobile systems. However, existing solutions require developers to directly program the low-power processors and carefully manage inter-processor communication. We present Reflex, a suite of compiler and runtime techniques that significantly lower the barrier for developers to leverage such low-power processors. The heart of Reflex is a software Distributed Shared Memory (DSM) that enables shared memory objects with release consistency among code running on loosely coupled processors. In order to achieve high energy efficiency without sacrificing performance much, the Reflex DSM leverages (i) extreme architectural asymmetry between low-power processors and powerful central processors, (ii) aggressive compile-time optimization, and (iii) a minimalist runtime that supports efficient message passing and event-driven execution. We report a complete realization of Reflex that runs on a TI OMAP4430-based development platform as well as on a custom tri-processor mobile platform. Using smartphone sensing applications reported in recent literature, we show that Reflex supports a programming style very close to contemporary smartphone programming. Compared to message passing, the Reflex DSM greatly reduces efforts in programming heterogeneous smartphones, eliminating up to 38% of the source lines of application code. Compared to running the same applications on existing smartphones, Reflex reduces the average system power consumption by up to 81%.

K2: a mobile operating system for heterogeneous coherence domains

Mobile System-on-Chips (SoC) that incorporate heterogeneous coherence domains promise high energy efficiency to a wide range of mobile applications, yet are difficult to program. To exploit the architecture, a desirable, yet missing capability is to replicate operating system (OS) services over multiple coherence domains with minimum inter-domain communication. In designing such an OS, we set three goals: to ease application development, to simplify OS engineering, and to preserve the current OS performance. To this end, we identify a shared-most OS model for multiple coherence domains: creating per-domain instances of core OS services with no shared state, while enabling other extended OS services to share state across domains. To test the model, we build K2, a prototype OS on the TI OMAP4 SoC, by reusing most of the Linux 3.4 source. K2 presents a single system image to applications with its two kernels running on top of the two coherence domains of OMAP4. The two kernels have independent instances of core OS services, such as page allocator and interrupt management, as coordinated by K2; the two kernels share most extended OS services, such as device drivers, whose state is kept coherent transparently by K2. Despite platform constraints and unoptimized code, K2 improves energy efficiency for light OS workloads by 8x-10x, while incurring less than 6% performance overhead for a device driver shared between kernels. Our experiences with K2 show that the shared-most model is promising.

Characterizing Smartphone Usage Patterns from Millions of Android Users

he prevalence of smart devices has promoted the popular- ity of mobile applications (a.k.a. apps) in recent years. A number of interesting and important questions remain unan- swered, such as why a user likes/dislikes an app, how an app becomes popular or eventually perishes, how a user selects apps to install and interacts with them, how frequently an app is used and how much traffic it generates, etc. This paper presents an empirical analysis of app usage behaviors collected from millions of users of Wandoujia, a leading An- droid app marketplace in China. The dataset covers two types of user behaviors of using over 0.2 million Android apps, including (1) app management activities (i.e., installa- tion, updating, and uninstallation) of over 0.8 million unique users and (2) app network traffic from over 2 million unique users. We explore multiple aspects of such behavior data and present interesting patterns of app usage. The results provide many useful implications to the developers, users, and disseminators of mobile apps.

SmartAds: bringing contextual ads to mobile apps

A recent study showed that while US consumers spent 30% more time on mobile apps than on traditional web, advertisers spent 1600% less money on mobile ads. One key reason is that unlike most web ad providers, todays mobile ads are not contextual---they do not take into account the content of the page they are displayed on. Thus, most mobile ads are irrelevant to what the user is interested in. For example, it is not uncommon to see gambling ads being displayed in a Bible app. This irrelevance results in low clickthrough rates, and hence advertisers shy away from the mobile platform. Using data from top 1200 apps in Windows Phone marketplace, and a one-week trace of ad keywords from Microsofts ad network, we show that content displayed by mobile apps is a potential goldmine of keywords that advertisers are interested in. However, unlike web pages, which can be crawled and indexed offline for contextual advertising, content shown on mobile apps is often either generated dynamically, or is embedded in the apps themselves; and hence cannot be crawled. The only solution is to scrape the content at runtime, extract keywords and fetch contextually relevant ads. The challenge is to do this without excessive overhead and without violating user privacy. In this paper, we describe a system called SmartAds to address this challenge. We have built a prototype of SmartAds for Windows Phone apps. In a large user study with over 5000 ad impressions, we found that SmartAds nearly doubles the relevance score, while consuming minimal additional resources and preserving user privacy.

Dandelion: a framework for transparently programming phone-centered wireless body sensor applications for health

Many innovative mobile health applications can be enabled by augmenting wireless body sensors to mobile phones, e.g. monitoring personal fitness with on-body accelerometer and EKG sensors. However, it is difficult for the majority of smartphone developers to program wireless body sensors directly; current sensor nodes require developers to master node-level programming, implement the communication between the smartphone and sensors, and even learn new languages. The large gap between existing programming styles for smartphones and sensors prevents body sensors from being widely adopted by smartphone applications, despite the burgeoning Apple App Store and Android Market. To bridge this programming gap, we present Dandelion1, a novel framework for developing wireless body sensor applications on smartphones. Dandelion provides three major benefits: 1) platform-agnostic programming abstraction for in-sensor data processing, called senselet, 2) transparent integration of senselets and the smartphone code, and 3) platform-independent development and distribution of senselets. We provide an implementation of Dandelion on the Maemo Linux smartphone platform and the Rice Orbit body sensor platform. We evaluate Dandelion by implementing real-world applications, and show that Dandelion effectively eliminates the programming gap and significantly reduces the development efforts. We further show that Dandelion incurs a very small overhead; in total less than 5% of the memory capacity and less than 3% of the processor time of a typical ultra low power sensor.

RhythmLink: securely pairing I/O-constrained devices by tapping

We present RhythmLink, a system that improves the wireless pairing user experience. Users can link devices such as phones and headsets together by tapping a known rhythm on each device. In contrast to current solutions, RhythmLink does not require user interaction with the host device during the pairing process; and it only requires binary input on the peripheral, making it appropriate for small devices with minimal physical affordances. We describe the challenges in enabling this user experience and our solution, an algorithm that allows two devices to compare imprecisely-entered tap sequences while maintaining the secrecy of those sequences. We also discuss our prototype implementation of RhythmLink and review the results of initial user tests.

memif : Towards Programming Heterogeneous Memory Asynchronously

To harness a heterogeneous memory hierarchy, it is advantageous to integrate application knowledge in guiding frequent memory move, i.e., replicating or migrating virtual memory regions. To this end, we present memif, a protected OS service for asynchronous, hardware-accelerated memory move. Compared to the state of the art -- page migration in Linux, memif incurs low overhead and low latency; in order to do so, it not only redefines the semantics of kernel interface but also overhauls the underlying mechanisms, including request/completion management, race handling, and DMA engine configuration. We implement memif in Linux for a server-class system-on-chip that features heterogeneous memories. Compared to the current Linux page migration, memif reduces CPU usage by up to 15% for small pages and by up to 38x for large pages; in continuously serving requests, memif has no need for request batching and reduces latency by up to 63%. By crafting a small runtime atop memif, we improve the throughputs for a set of streaming workloads by up to 33%. Overall, memif has opened the door to software management of heterogeneous memory.