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Full-Text Articles in Physical Sciences and Mathematics

Edge-Cloud Iot Data Analytics: Intelligence At The Edge With Deep Learning, Ananda Mohon M. Ghosh May 2020

Edge-Cloud Iot Data Analytics: Intelligence At The Edge With Deep Learning, Ananda Mohon M. Ghosh

Electronic Thesis and Dissertation Repository

Rapid growth in numbers of connected devices, including sensors, mobile, wearable, and other Internet of Things (IoT) devices, is creating an explosion of data that are moving across the network. To carry out machine learning (ML), IoT data are typically transferred to the cloud or another centralized system for storage and processing; however, this causes latencies and increases network traffic. Edge computing has the potential to remedy those issues by moving computation closer to the network edge and data sources. On the other hand, edge computing is limited in terms of computational power and thus is not well suited for …


A Visual Analytics System For Making Sense Of Real-Time Twitter Streams, Amir Haghighatimaleki Jan 2020

A Visual Analytics System For Making Sense Of Real-Time Twitter Streams, Amir Haghighatimaleki

Electronic Thesis and Dissertation Repository

Through social media platforms, massive amounts of data are being produced. Twitter, as one such platform, enables users to post “tweets” on an unprecedented scale. Once analyzed by machine learning (ML) techniques and in aggregate, Twitter data can be an invaluable resource for gaining insight. However, when applied to real-time data streams, due to covariate shifts in the data (i.e., changes in the distributions of the inputs of ML algorithms), existing ML approaches result in different types of biases and provide uncertain outputs. This thesis describes a visual analytics system (i.e., a tool that combines data visualization, human-data interaction, and …


Secured Data Masking Framework And Technique For Preserving Privacy In A Business Intelligence Analytics Platform, Osama Ali Dec 2018

Secured Data Masking Framework And Technique For Preserving Privacy In A Business Intelligence Analytics Platform, Osama Ali

Electronic Thesis and Dissertation Repository

The main concept behind business intelligence (BI) is how to use integrated data across different business systems within an enterprise to make strategic decisions. It is difficult to map internal and external BI’s users to subsets of the enterprise’s data warehouse (DW), resulting that protecting the privacy of this data while maintaining its utility is a challenging task. Today, such DW systems constitute one of the most serious privacy breach threats that an enterprise might face when many internal users of different security levels have access to BI components. This thesis proposes a data masking framework (iMaskU: Identify, Map, Apply, …


Machs: Mitigating The Achilles Heel Of The Cloud Through High Availability And Performance-Aware Solutions, Manar Jammal Apr 2017

Machs: Mitigating The Achilles Heel Of The Cloud Through High Availability And Performance-Aware Solutions, Manar Jammal

Electronic Thesis and Dissertation Repository

Cloud computing is continuously growing as a business model for hosting information and communication technology applications. However, many concerns arise regarding the quality of service (QoS) offered by the cloud. One major challenge is the high availability (HA) of cloud-based applications. The key to achieving availability requirements is to develop an approach that is immune to cloud failures while minimizing the service level agreement (SLA) violations. To this end, this thesis addresses the HA of cloud-based applications from different perspectives. First, the thesis proposes a component’s HA-ware scheduler (CHASE) to manage the deployments of carrier-grade cloud applications while maximizing their …


Metafork: A Compilation Framework For Concurrency Models Targeting Hardware Accelerators, Xiaohui Chen Mar 2017

Metafork: A Compilation Framework For Concurrency Models Targeting Hardware Accelerators, Xiaohui Chen

Electronic Thesis and Dissertation Repository

Parallel programming is gaining ground in various domains due to the tremendous computational power that it brings; however, it also requires a substantial code crafting effort to achieve performance improvement. Unfortunately, in most cases, performance tuning has to be accomplished manually by programmers. We argue that automated tuning is necessary due to the combination of the following factors. First, code optimization is machine-dependent. That is, optimization preferred on one machine may be not suitable for another machine. Second, as the possible optimization search space increases, manually finding an optimized configuration is hard. Therefore, developing new compiler techniques for optimizing applications …


Climbing Up Cloud Nine: Performance Enhancement Techniques For Cloud Computing Environments, Mohamed Abusharkh Jul 2016

Climbing Up Cloud Nine: Performance Enhancement Techniques For Cloud Computing Environments, Mohamed Abusharkh

Electronic Thesis and Dissertation Repository

With the transformation of cloud computing technologies from an attractive trend to a business reality, the need is more pressing than ever for efficient cloud service management tools and techniques. As cloud technologies continue to mature, the service model, resource allocation methodologies, energy efficiency models and general service management schemes are not yet saturated. The burden of making this all tick perfectly falls on cloud providers. Surely, economy of scale revenues and leveraging existing infrastructure and giant workforce are there as positives, but it is far from straightforward operation from that point. Performance and service delivery will still depend on …


On The Interoperability Of Programming Languages Based On The Fork-Join Parallelism Model, Sushek Shekar Dec 2013

On The Interoperability Of Programming Languages Based On The Fork-Join Parallelism Model, Sushek Shekar

Electronic Thesis and Dissertation Repository

This thesis describes the implementation of MetaFork, a meta-language for concurrency platforms targeting multicore architectures. First of all, MetaFork is a multithreaded language based on the fork-join model of concurrency: it allows the programmer to express parallel algorithms assuming that tasks are dynamically scheduled at run-time. While MetaFork makes no assumption about the run-time system, it formally defines the serial C-elision of a MetaFork program. In addition, MetaFork is a suite of source-to-source compilers permitting the automatic translation of multithreaded programs between programming languages based on the fork-join model. Currently, this compilation framework supports the OpenMP and CilkPlus concurrency platforms. …


Collaborative Policy-Based Autonomic Management In Iaas Clouds, Omid Mola Sep 2013

Collaborative Policy-Based Autonomic Management In Iaas Clouds, Omid Mola

Electronic Thesis and Dissertation Repository

With the increasing number of "machines" (either virtual or physical) in a computing environment, it is becoming harder to monitor and manage these resources. Relying on human administrators, even with tools, is expensive and the growing complexity makes management even harder. The alternative is to look for automated approaches that can monitor and manage computing resources in real time with no human intervention. One of the approaches to this problem is policy-based autonomic management. However, in large systems having one single autonomic manager to manage everything is almost impossible. Therefore, multiple autonomic managers will be needed and these will need …