Managing big data experiments on smartphones

The explosive number of smartphones with ever growing sensing and computing capabilities have brought a paradigm shift to many traditional domains of the computing field. Re-programming smartphones and instrumenting them for application testing and data gathering at scale is currently a tedious and time-consuming process that poses significant logistical challenges. Next generation smartphone applications are expected to be much larger-scale and complex, demanding that these undergo evaluation and testing under different real-world datasets, devices and conditions. In this paper, we present an architecture for managing such large-scale data management experiments on real smartphones. We particularly present the building blocks of our architecture that encompassed smartphone sensor data collected by the crowd and organized in our big data repository. The given datasets can then be replayed on our testbed comprising of real and simulated smartphones accessible to developers through a web-based interface. We present the applicability of our architecture through a case study that involves the evaluation of individual components that are part of a complex indoor positioning system for smartphones, coined Anyplace, which we have developed over the years. The given study shows how our architecture allows us to derive novel insights into the performance of our algorithms and applications, by simplifying the management of large-scale data on smartphones

Managing Smartphone Testbeds with SmartLab

The explosive number of smartphones with ever growing sensing and computing capabilities have brought a paradigm shift to many traditional domains of the computing field. Re-programming smartphones and instrumenting them for application testing and data gathering at scale is currently a tedious and time-consuming process that poses significant logistical challenges. In this paper, we make three major contributions: First, we propose a comprehensive architecture, coined SmartLab1, for managing a cluster of both real and virtual smartphones that are either wired to a private cloud or connected over a wireless link. Second, we propose and describe a number of Android management optimizations (e.g., command pipelining, screen-capturing, file management), which can be useful to the community for building similar functionality into their systems. Third, we conduct extensive experiments and microbenchmarks to support our design choices providing qualitative evidence on the expected performance of each module comprising our architecture. This paper also overviews experiences of using SmartLab in a research-oriented setting and also ongoing and future development efforts

SmartLab: Empowering Mobile Computing Research through an Open Smartphone Cloud

SmartLab is a first-of-a-kind open cloud of smartphones that enables a new line of systems-oriented mobile computing research

Efficient and Reliable Filesystem Snapshot Distribution

Linux is an portable operating system kernel devised by Linus Torvalds and it can be used in conjunction with other userspace utilities such as GNU to build a free and open-source operating system for a multitude of target applications. While Linux-based operating systems have made significant progress on the servers and embedded systems, there is still much room for improvement for workstations and laptops. Up to now Linux-based operating system deployment has been error prone, time-consuming process and usually specific to a particular distribution of Linux. Linux-based operating systems also have a reputation of being overly complex to set up for a novice computer user and even though there are now laptops available with pre-installed Ubuntu [1], installing Linux-based operating system on arbitrary device is troublesome due to lack of native support for certain hardware components. In this thesis Butterknife, a B-tree file system (Btrfs) and Linux Containers (LXC) based provisioning suite is presented. Butterknife can be used to significantly reduce deployment time of customized Linuxbased operating system. Butterknife makes use of LXC to prepare a template of the root filesystem and Btrfs snapshotting to save state of the template. Btrfs send/receive mechanism is then used to transfer the root filesystem to the target machine. Post-deployment scripts are then used to configure the root filesystem for particular deployment, optionally retaining hostname, domain membership, configuration management keys etc. Current implementation of Butterknife uses HTTP(S) and multicast for transport, and various peer-to-peer scenarios are discussed in the Section 6 – Conclusions and Future Work. In addition to provisioning, Butterknife makes use of Btrfs incremental snapshots to implement differential upgrades. This approach is especially attractive for mobile devices, embedded systems and Internet of Things, where software upgrades have to be delivered in a guaranteed manner. Butterknife brings additional value to already existing ecosystem by bridging gap between stock installation medium and configuration management