Browsing by Subject "Cloud"
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Item Cerberus : a cloud-based environmental data aggregator(2013-08) Rosas, Rodolfo; Aziz, AdnanIT professionals must constantly ensure the integrity and availability of their services. One aspect to monitor is the physical environment surrounding their equipment. Factors such as high temperature, humidity or water leaks can all contribute to costly downtime. There are a variety of solutions for monitoring these factors but those which can make their data universally available are of particular interest. The more cost- effective alternatives on the market are found as embedded devices with integrated web servers. The drawbacks of these systems have been their resource limitations as well as the need for complex configuration to make their data available from any location. A solution based in the cloud could remove the resource constraints of embedded systems and easily achieve widespread availability. This report presents Cerberus, a cloud-based environmental data aggregator that allows web server based devices to bypass their limitations and the necessary configuration to achieve widespread availability. It was implemented using two distinct cloud platforms and has been in active use for several months. Cerberus allows for environment monitors to push their data in as little as 250 ms while allowing for dynamic scaling as needed. The application provides all the necessary functionality such as alarm v generation, data visualization and archiving. The following presents the conception, design, implementation and future extensions to Cerberus as well as a comparative study of different cloud-based hosting services.Item Revolver : synchronized visual event capture using mobile devices and cloud services(2012-12) Stathopoulos, Michael; Khurshid, Sarfraz; Aziz, AdnanThe proliferation of mobile computing devices with powerful sensing and communication capabilities has created an immense social landscape of awareness and connectedness. Social media applications have been largely designed for asynchronous expression and collaboration among individuals. Though these models have served as suitable surrogates for social interaction in a rapidly evolving digital age, they have been insufficient at connecting people spatially and temporally. This report describes Revolver: an appli- cation utilizing the state-of-the-art in mobile and distributed computing to provide users with a shared sense of time and space. Revolver allows users to synchronously capture image data of their surroundings with the ability to virtually reconstruct an event from the separate sources. We present the ratio- nale for the project, design considerations, implementation details, results of the prototyping effort, and conclusions to carry this project to future phases of development for viable deployment.Item The Evolution of the Physicochemical Properties of Aerosols in the Atmosphere(2011-02-22) Tomlinson, JasonA Differential Mobility Analyzer/Tandem Differential Mobility Analyzer (DMA/TDMA) system was used to measure simultaneously the size distribution and hygroscopicity of the ambient aerosol population. The system was operated aboard the National Center for Atmospheric Research/National Science Foundation (NCAR/NSF) C-130 during the 2006 Megacity Initiative: Local and Global Research Observations (MILAGRO) field campaign followed by the 2006 Intercontinental Chemical Transport Experiment ? Phase B (INTEX-B) field campaign. The research flights for the MILAGRO campaign were conducted within the Mexico City basin and the region to the northeast within the pollution plume. The aerosol within the basin is dominated by organics with an average measured kappa value of 0.21 /- 0.18, 0.13 /- 0.09, 0.09 /- 0.06, 0.14 /- 0.07, and 0.17 /- 0.04 for dry particle diameters of 0.025, 0.050, 0.100, 0.200, and 0.300 mu m, respectively. As the aerosols are transported away from the Mexico City Basin, secondary organic aerosol formation through oxidation and condensation of sulfate on the aerosols surface rapidly increases the solubility of the aerosol. The most pronounced change occurs for a 0.100 mu m diameter aerosol where, after 6 hours of transport, the average kappa value increased by a factor of 3 to a kappa?of 0.29 /- 0.13. The rapid increase in solubility increases the fraction of the aerosol size distribution that could be activated within a cloud. The research flights for the INTEX-B field campaign investigated the evolution of the physicochemical properties of the Asian aerosol plume after 3 to 7 days of transport. The Asian aerosol within the free troposphere exhibited a bimodal growth distribution roughly 50 percent of the time. The more soluble mode of the growth distribution contributed between 67-80 percent of the overall growth distribution and had an average kappa?between 0.40 and 0.53 for dry particle diameters of 0.025, 0.050, 0.100, and 0.300 mu m. The secondary mode was insoluble with an average kappa?between 0.01 and 0.05 for all dry particle diameters. Cloud condensation nuclei closure was attained at a supersaturation of 0.2 percent for all particles within the free troposphere by either assuming a pure ammonium bisulfate composition or a binary composition of ammonium bisulfate and an insoluble organic.Item Thin Cloud Length Scales Using CALIPSO and CloudSat Data(2010-10-12) Solbrig, Jeremy E.Thin clouds are the most difficult cloud type to observe. The recent availability of joint cloud products from the active remote sensing instruments aboard CloudSat and the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite (CALIPSO) facilitates the study of these clouds. Using one of these joint cloud products, 2B-GEOPROF-Lidar, and a post-processing algorithm designed to find horizontally continuous thin clouds within the cloud product, the locations, length scales, and vertical distributions by length of thin clouds are determined. It is found that thin clouds vary in length from a few km to over 2900 km and tend to be longer in the tropical upper troposphere than lower in the atmosphere and at higher latitudes. In the upper troposphere between 0? and 40?N, over 20% of all thin cloud measurements in the 2B-GEOPROF-Lidar product are contributed by thin clouds that are longer than 500 km. In fact, in this latitude range, over 65% of all thin cloud measurements are contributed by clouds longer than 100 km. Also, thin cloud length and frequency differ between the four seasons in the year of data used here.Item Towards a privacy-preserving platform for apps(2014-12) Lee, Sangmin; Dahlin, MichaelOn mobile platforms such as iOS and Android, Web browsers such as Google Chrome, and even smart televisions such as Google TV or Roku, hundreds of thousands of software apps provide services to users. Their functionality often requires access to potentially sensitive user data (e.g., contact lists, passwords, photos), sensor inputs (e.g., camera, microphone, GPS), and/or information about user behavior. Most apps use this data responsibly, but there has also been evidence of privacy violations. As a result, individuals must carefully consider what apps to install and corporations often restrict what apps employees can install on their devices, to prevent an untrusted app—or a cloud provider that an app communicates with—from leaking personal data and proprietary information. There is an inherent trade-off between users’ privacy and apps’ functionality. An app with no access to user data cannot leak anything sensitive, but many apps cannot function without such data. A password management app needs access to passwords, an audio transcription app needs access to the recordings of users’ speech, and a navigation app needs users’ location. In this dissertation, we present two app platform designs, πBox and CleanRoom, that strike a useful balance between users’ privacy and apps’ functional needs, thus shifting much of the responsibility for protecting privacy from the app and its users to the platform itself. πBox is a new app platform that prevents apps from misusing information about their users. To achieve this, πBox deploys (1) a sandbox that spans the user’s device and the cloud, (2) specialized storage and communication channels that enable common app functionality, and (3) an adaptation of recent theoretical algorithms for differential privacy under continual observation. We describe a prototype implementation of πBox and show how it enables a wide range of useful apps with minimal performance overhead and without sacrificing user privacy. In particular, πBox develops the aforementioned three techniques under the assumption of limited sharing of personal data. CleanRoom extends πBox and is designed to protect confidentiality in a "Bring Your Own Apps" (BYOA) world in which employees use their own untrusted third-party apps to create, edit, and share corporate data. CleanRoom’s core guarantee is privacy-preserving collaboration: CleanRoom enables employees to work together on shared documents while ensuring that the documents’ owners—not the app accessing the document—control who can access and collaborate on the document. To achieve this guarantee, CleanRoom partitions an app into three parts, each of which implements a different function of the app (data navigation, data manipulation, and app settings), and controls communication between these parts. We show that CleanRoom accommodates a broad range of apps, preserves the confidentiality of the data that these apps access, and incurs insignificant overhead (e.g., 0.11 ms of overhead per client-server request). Both πBox and CleanRoom use differential privacy for apps to provide feedback to their publisher. This dissertation explores how to adapt differential privacy to be useful for app platforms. In particular, we investigate an adaptation of re- cent theoretical algorithms for differential privacy under continual observation and several techniques to leverage it for useful features in an app environment including advertising, app performance feedback, and error reporting.Item Vertical Distribution of Cloud Liquid Water and Ice: A Comparison of MODIS Satellite Observations and the GISS Global Climate Model(2015-02-09) Pitts, Katherine LClouds continue to be a large source of uncertainty within global climate models. While satellites provide the only global datasets for comparison with these models, satellite retrievals provide inferences of cloud properties, rather than direct measurements. Therefore, comparisons between climate model simulations and satellite retrievals require careful construction of globally-gridded and time-averaged (Level 3) satellite datasets. For some types of comparisons, existing Level 3 datasets may not be sufficient, necessitating the generation of gridded datasets directly from Level 2 products. The current study uses a filtering and gridding algorithm to create a customized globally-gridded (i.e., Level 3) dataset based on Aqua MODIS Level 2 cloud top pressure and cloud optical property retrievals. With the recent release of MODIS Collection 6, we utilize this algorithm to examine the differences between cloud parameters in the MODIS Collection 5 and Collection 6 datasets, and then compare these satellite measurements to the GISS-E2-H model-simulated cloud parameters that were provided for the Coupled Model Intercomparison Project - Phase 5 (CMIP5). This comparison study focuses on the vertical distribution of cloud liquid water and ice, especially in the mid-troposphere where mixed-phase clouds are most likely to occur. Results show that the cloud retrieval algorithm improvements with MODIS Collection 6 lead to an overall decrease in uncertainty in cloud water path retrievals, as well as a change in the vertical distribution of clouds (high clouds higher, low clouds lower) and the resulting vertical distribution of cloud water path (increased mid-level cloud water path). When MODIS Collection 6 data are compared with GISS-E2-H climate model simulations, it is clear that the model greatly overestimates ice water path within a double ITCZ (intertropical convergence zone) in the high cloud height regime, but underestimates ice water path in higher latitudes. The model also overestimates low level liquid water path over land, especially over mountainous regions. The filtering and gridding algorithm used in this study is a convenient tool for building custom gridded datasets to address research questions that the official Level 3 datasets were not designed for.