With the continued proliferation of drones, unmanned aerial vehicles, additional uses for them are growing and the demand for their services is on the rise. We present AnDrone, a drone-as-a-service solution that makes drones accessible in the cloud. AnDrone pairs a cloud service with the first drone virtualization architecture. This enables a physical drone to run multiple virtual drones simultaneously in an isolated and secure manner at little additional cost, as computational costs are cheap compared to the operational and energy costs of putting a drone in the air. AnDrone virtualizes drones using a novel Linux container architecture. Android Things virtual drone containers provide a familiar user and development environment that can run existing Android apps. A real-time Linux flight controller container supports existing drone flight software and provides virtual drones with geofenced flight control. A device container transparently multiplexes access from virtual drones to a full range of drone hardware devices, including cameras and other sensors. Upon flight completion, virtual drones and their data can be uploaded to the cloud for offline access. We have implemented an AnDrone prototype based on Raspberry Pi 3 drone hardware. We demonstrate that it incurs minimal runtime performance and energy overhead, supports real-time virtual drone flight control, and runs untrusted third-party software in virtual drones in a secure manner while ensuring that the service provider maintains control of the drone hardware.

As smartphones and tablets proliferate, there is a growing demand for multi-mobile computing, the ability to combine multiple mobile systems into more capable ones. We present M2, a system for multi-mobile computing that enables existing unmodified mobile apps to share and combine multiple devices, including cameras, displays, speakers, microphones, sensors, GPS, and input. M2 introduces a new data-centric approach that leverages higher-level device abstractions and hardware acceleration to efficiently share device data, not API calls. To support heterogeneous devices, M2 introduces device transformation, a new technique to mix and match different types of devices. Example transformations include combining multiple displays into a single larger display for better viewing, or substituting accelerometer for touchscreen input to provide a Nintendo Wii-like experience with existing mobile gaming apps. We have implemented M2 and show that it (1) operates across heterogeneous systems, including multiple versions of Android and iOS, (2) can enable unmodified Android apps to use multiple mobile devices in new and powerful ways, including supporting users with disabilities and better audio conferencing, and (3) can run apps across mobile systems with modest overhead and qualitative performance indistinguishable from using local device hardware.

As smartphones and tablets proliferate, there is a growing demand for multi-mobile computing [1, 2], the ability to combine multiple commodity mobile systems into more capable ones, including using multiple hardware devices such as cameras, displays, speakers, microphones, sensors, GPS, and input. However, the tremendous device, hardware, and software heterogeneity of mobile systems makes this difficult. In this demo, we present M2, a system for multi-mobile computing that enables existing unmodified mobile apps to make use of new ways of sharing and combining multiple devices. M2 introduces a new data-centric approach that leverages higher-level device abstractions and encoding/decoding hardware to efficiently share device data as opposed to low-level device-specific APIs.

With the continued proliferation of mobile devices, apps will increasingly become multi-surface, running seamlessly across multiple user devices (e.g., phone, tablet, etc.). Yet general systems support for multi-surface app is limited to (1) screencasting, which relies on a single master device's computing power and battery life or (2) cloud backing, which is unsuitable in the face of disconnected operation or untrusted cloud providers. We present an alternative approach: Flux, an Android-based system that enables any app to become multi-surface through app migration. Flux overcomes device heterogeneity and residual dependencies through two key mechanisms. Selective Record/Adaptive Replay records just those device-agnostic app calls that lead to the generation of app-specific device-dependent state in system services and replays them on the target. Checkpoint/Restore in Android (CRIA) transitions an app into a state in which device-specific information can be safely discarded before checkpointing and restoring the app. Our implementation of Flux can migrate many popular, unmodified Android apps---including those with extensive device interactions like 3D accelerated graphics---across heterogeneous devices and is fast enough for interactive use.

We present Cider, an operating system compatibility architecture that can run applications built for different mobile ecosystems, iOS or Android, together on the same smartphone or tablet. Cider enhances the domestic operating system, Android, of a device with kernel-managed, per-thread personas to mimic the application binary interface of a foreign operating system, iOS, enabling it to run unmodified foreign binaries. This is accomplished using a novel combination of binary compatibility techniques including two new mechanisms: compile-time code adaptation, and diplomatic functions. Compile-time code adaptation enables existing unmodified foreign source code to be reused in the domestic kernel, reducing implementation effort required to support multiple binary interfaces for executing domestic and foreign applications. Diplomatic functions leverage per-thread personas, and allow foreign applications to use domestic libraries to access proprietary software and hardware interfaces. We have built a Cider prototype, and demonstrate that it imposes modest performance overhead and runs unmodified iOS and Android applications together on a Google Nexus tablet running the latest version of Android.

Smartphones are increasingly ubiquitous, and many users carry multiple phones to accommodate work, personal, and geographic mobility needs. We present Cells , a virtualization architecture for enabling multiple virtual smartphones to run simultaneously on the same physical cellphone in an isolated, secure manner. Cells introduces a usage model of having one foreground virtual phone and multiple background virtual phones. This model enables a new device namespace mechanism and novel device proxies that integrate with lightweight operating system virtualization to multiplex phone hardware across multiple virtual phones while providing native hardware device performance. Cells virtual phone features include fully accelerated 3D graphics, complete power management features, and full telephony functionality with separately assignable telephone numbers and caller ID support. We have implemented a prototype of Cells that supports multiple Android virtual phones on the same phone. Our performance results demonstrate that Cells imposes only modest runtime and memory overhead, works seamlessly across multiple hardware devices including Google Nexus 1 and Nexus S phones, and transparently runs Android applications at native speed without any modifications.

Smartphones are increasingly ubiquitous, and many users carry multiple phones to accommodate work, personal, and geographic mobility needs. We present Cells, a virtualization architecture for enabling multiple virtual smartphones to run simultaneously on the same physical cellphone in an isolated, secure manner. Cells introduces a usage model of having one foreground virtual phone and multiple background virtual phones. This model enables a new device namespace mechanism and novel device proxies that integrate with lightweight operating system virtualization to multiplex phone hardware across multiple virtual phones while providing native hardware device performance. Cells virtual phone features include fully accelerated 3D graphics, complete power, management features, and full telephony functionality with separately assignable telephone numbers and caller ID support. We have implemented a prototype of Cells that supports multiple Android virtual phones on the same phone. Our performance results demonstrate that Cells imposes only modest runtime and memory overhead, works seamlessly across multiple hardware devices including Google Nexus 1 and Nexus S phones, and transparently runs Android applications at native speed without any modifications.