Taeyeon Ki

PhoneLab: A Large Programmable Smartphone Testbed

As smartphones have emerged as the most widely deployed mobile computing platform, the scale of smartphone experimentation has lagged behind. New facilities enabling large-scale experiments are needed to ensure that research discoveries translate to the billions of smartphones in use today. To meet this challenge, we introduce PhoneLab, a 288-device smartphone testbed deployed at the University at Buffalo. PhoneLab provides access to smartphone users incentivized to participate in experiments while simplifying experiment data collection. The testbed will open for public experimentation in October, 2013, and continue to expand in 2014. To demonstrate the power of PhoneLab, we present three selected results from a usage characterization experiment run on 115 phones for 21 days. We use each result to motivate a future PhoneLab experiment, demonstrating how PhoneLab will enable mobile systems research.

PocketParker: pocketsourcing parking lot availability

Searching for parking spots generates frustration and pollution. To address these parking problems, we present PocketParker, a crowdsourcing system using smartphones to predict parking lot availability. PocketParker is an example of a subset of crowdsourcing we call pocketsourcing. Pocketsourcing applications require no explicit user input or additional infrastructure, running effectively without the phone leaving the users pocket. PocketParker detects arrivals and departures by leveraging existing activity recognition algorithms. Detected events are used to maintain per-lot availability models and respond to queries. By estimating the number of drivers not using PocketParker, a small fraction of drivers can generate accurate predictions. Our evaluation shows that PocketParker quickly and correctly detects parking events and is robust to the presence of hidden drivers. Camera monitoring of several parking lots as 105 PocketParker users generated 10;827 events over 45 days shows that PocketParker was able to correctly predict lot availability 94% of the time.

Demo: Reptor: Enabling API Virtualization on Android for Platform Openness

This paper proposes a new technique that enables open innovation in mobile platforms. Our technique allows third-party developers to modify, instrument, or extend platform API calls and deploy their modifications seamlessly. The uniqueness of our technique is that it enables modifications completely at the app layer without requiring any platform-level changes. This allows practical openness---third parties can easily distribute their modifications for a platform without the need to update the entire platform. To demonstrate the benefits of our technique, we have developed a prototype on Android called Reptor and used it to instrument real-world apps with novel functionality. Our evaluation in realistic scenarios shows that Reptor has little overhead in performance and energy, and only modest overhead in memory usage that ranges from 0.6% to 10% for the observed worst cases.

Demo: BlueMountain: An Architecture to Customize Data Management on Mobile Systems

BlueMountain is a system that enables building pluggable data management solutions which can be linked with any Android app at runtime, without requiring any modifications to the Android platform. BlueMountain simplifies the app development, provides flexibility to end users, and works with existing apps.

BlueMountain: An Architecture for Customized Data Management on Mobile Systems

In this paper, we design a pluggable data management solution for modern mobile platforms (e.g., Android). Our goal is to allow data management mechanisms and policies to be implemented independently of core app logic. Our design allows a user to install data management solutions as apps, install multiple such solutions on a single device, and choose a suitable solution each for one or more apps. It allows app developers to focus their effort on app logic and helps the developers of data management solutions to achieve wider deployability. It also gives increased control of data management to end users and allows them to use different solutions for different apps. We present a prototype implementation of our design called BlueMountain, and implement several data management solutions for file and database management to demonstrate the utility and ease of using our design. We perform detailed microbenchmarks as well as end-to-end measurements for files and databases to demonstrate the performance overhead incurred by our implementation.

System-E: Enhancing Privacy on Mobile Systems through Content-Based Classification and Storage

Mobile systems face privacy challenges including coarsegrained privacy control and the inability to distinguish private and public files. We propose System-E, a novel system which can enhance the user privacy on mobile systems (e.g., Android) by (1) enabling users to set finer grained permissions for apps accessing data, and (2) enabling automatic classification of data (e.g., photos) at the storage layer (e.g., by using deep learning) to prevent potentially sensitive data from being stored/accessed with open permissions.

Duvel: Enabling Context-driven, Multi-profile Apps on Android through Storage Sandboxing

We present a novel technique to achieve a dynamic, context-driven, multiple-profile manager for individual apps on stock Android. Our system allows users to use a single app with any number of accounts, allows incognito modes for every app, and allows a context-driven dynamic switching between the profiles (e.g., based on geolocation). Our technique achieves this by creating a sandboxed storage environment within each app through byte-code instrumentation. This allows for a clean separation of profile specific data and allows users to run personal and business accounts on the same phone, or sandbox an app in incognito mode without sharing any data between them. We present many more use cases where our solution can be used to improve user experience on mobile systems. In contrast to many of the existing solutions, our solution eliminates any modifications to the platform, does not require any special SDK to develop apps, and can use a context-driven policy to dynamically switch between profiles. We realize a storage sandbox environment called Duvel on Android, based on our previous work BlueMountain, and show how Duvel can enable using multiple accounts and incognito mode in popular apps.

Demo: Enabling Dynamic Gesture Mapping with UI Events

We demonstrate Gesto, a dynamic gesture mapping tool. It provides users to map any gesture to a certain UI event that the users need. Also, the mapping can be easily changed by users.

Demo: Fully Automated UI Testing System for Large-scale Android Apps Using Multiple Devices

We demonstrate AutoClicker, a fully automated UI testing system for large-scale Android apps using multiple devices. It provides a way to quickly and easily verify that a large number of Android apps behave correctly at runtime in a repeatable manner.

Demo: API Virtualization for Platform Openness in Android

We propose a novel technique called API virtualization to enable open innovation in Android. API virtualization inserts a shim layer between the Android platform layer and the app layer as shown in Figure 1, which can intercept any and every platform API call made by an app. In addition, API virtualization allows third-party developers to inject custom code, so that they can modify, reimplement, or customize existing Android APIs. This is achieved by (i) injecting a wrapper class for each platform API class that a third-party developer wants to replace, and (ii) rewriting the binary of an app so that the app code uses wrapper classes instead of platform API classes. Our API virtualization is motivated by the lack of openness in mobile systems at the platform level. For example, Android is known to be an open platform since the source code is open; thirdparty developers easily access and modify the source. However, when it comes to deploying their platform-level modifications, there is a stiff barrier. Only Google and other mobile vendors such as Samsung, LG, etc. have the privilege to distribute platform modifications at a large scale. In other words, there are only a select few players who can control the innovation on Android.