Browsing by Author "Taylor, Daniel"

Now showing 1 - 4 of 4
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    Developing a Low-Cost UAV Avionics Package
    (2012-04-18) Taylor, Daniel
    The term 'unmanned Aerial Vehicle' (UAV) refers to flying vehicles not populated with humans. They are frequently used by a variety of groups, including the military, scientific researchers, and search-and-rescue workers to do things and go places that are impossible, dangerous, or just inconvenient for humans. The cost of these UAVs, however, is prohibitive in many cases. The UAV Research Group at the University of Minnesota is working on a low-cost UAV platform to alleviate this problem. The off-the-shelf components used to keep costs down, however, come with limited capabilities. Addressed here is the limited sensor and actuator connectivity available on the board used by the group. By creating an add-on board to read and write to sensors and actuators, we expanded the number of parts that can be added to the UAV, making this low-cost solution more feasible for practical applications.
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    GPU-based digital hologram reconstruction and particle detection
    (2014-12) Taylor, Daniel
    Digital holograms, when combined with tracer particles, can be used for examining otherwise-invisible fluid flows. These holograms can be captured with standard digital imaging equipment, however processing them to extract tracer or particle locations is computationally expensive. Exacerbating the issue is that hundreds or thousands of holograms must be reconstructed to analyze a single flow.Presented here is a hologram reconstruction and particle extraction system exploiting the massive parallelism of graphics processing units (GPUs) to reduce the time required to locate the particles in 3D space by orders of magnitude. This system requires no expensive proprietary hardware and runs on standard computers, with the only special requirement being an off-the-shelf Nvidia GPU.
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    Mobility management in cellular telephony
    (2002-07) Cooke, Benjamin P.; Kwon, Darongsae; Glotov, Dmitry; Schurr, Simon; Taylor, Daniel; Wittman, Todd; Shallcross, David F.(mentor)
    In the world of cellular telephony there is a hierarchy of controlling devices. Cellular telephones communicate with Base Transceiver Satations (BTS) or transceivers, which is turn are assigned to Base Station Controllers (BSC) or controllers. All controllers are connected to a Mobile Switching Centers (MSC). As a user of a cellular telephone moves around, the call must be transfered from transceiver to transceiver, and sometimes from controller to controller. We are interested in the problem of minimizing the cost of these transfers from controller to controller. In the above hierarchy, we consider a subtree emanating from one Mobile Switching Center. The two sets corresponding to the subtree are I, the set of transceivers, and J, the set of controllers. The problem is to assign each transceiver from the set I to a controller from the set J optimally subject to certain constraints...
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    Mobilizing the Cloud: Enabling Multi-User Mobile Outsourcing in the Cloud
    (2011-11-21) Mei, Chonglei; Taylor, Daniel; Wang, Chenyu; Chandra, Abhishek; Weissman, Jon
    Mobile devices, such as smartphones and tablets, are becoming the universal interface to online services and applications. However, such devices have limited computational power and battery life, which limits their ability to execute rich, resource-intensive applications. Mobile computation outsourcing to external resources has been proposed as a technique to alleviate this problem. Most existing work on mobile outsourcing has focused either on single application optimization, or outsourcing to fixed, local resources, with the assumption that wide-area latency is prohibitively high. In this paper, we present the design and implementation of an Android/Amazon EC2-based mobile application outsourcing platform, leveraging the cloud for scalability, elasticity, and multi-user code/data sharing. Using this platform, we empirically demonstrate that the cloud is not only feasible but desirable as an offloading platform for latency tolerant applications despite wide-area latencies. Our platform is designed to dynamically scale to support a large number of mobile users concurrently by utilizing the elastic provisioning capabilities of the cloud, as well as by allowing reuse of common code components across multiple users. Additionally, we have developed techniques for detecting data sharing across multiple applications, and proposed novel scheduling algorithms that exploit such data sharing for better scalability and user performance. Experiments with our offloading platform show that our proposed techniques and algorithms substantially improve application performance, while achieving high efficiency in terms of resource and network usage.