Physical Sciences and Mathematics Commons^™

Towards Digital Twins For Optimizing Metrics In Distributed Storage Systems - A Review, May Itani, Layal Abu Daher, Ahmad Hammoud

BAU Journal - Science and Technology

With the exponential data growth, there is a crucial need for highly available, scalable, reliable, and cost-effective Distributed Storage Systems (DSSs). To ensure such efficient and fault tolerant systems, replication and erasure coding techniques are typically used in traditional DSSs. However, these systems are prone to failure and require different failure prevention and recovery algorithms. Failure recovery of DSS and data reconstruction techniques take into consideration different performance metrics optimization in the recovery process. In this paper, DSS performance metrics are introduced. Several recent papers related to adopting erasure coding in DSSs are surveyed together with highlighting related performance metrics …

Fault Aware Task Scheduling In Cloud Using Min-Min And Dbscan, S. M.F.D.Syed Mustapha, Punit Gupta

All Works

Cloud computing leverages computing resources by managing these resources globally in a more efficient manner as compared to individual resource services. It requires us to deliver the resources in a heterogeneous environment and also in a highly dynamic nature. Hence, there is always a risk of resource allocation failure that can maximize the delay in task execution. Such adverse impact in the cloud environment also raises questions on quality of service (QoS). Resource management for cloud application and service have bigger challenges and many researchers have proposed several solutions but there is room for improvement. Clustering the resources clustering and …

Technology Manufacturing Leaders’ Innovation Strategies To Improve Users’ Choice Capabilities In A Fast-Changing Markets, Magnus Ekwunife

Walden Dissertations and Doctoral Studies

Some leaders of technology manufacturing organizations lack strategies to educate their users on how to make the optimal cloud technology selection decisions for their organizations during rapidly evolving innovation, resulting in significant risk of wrong choices and loss of customer loyalty. Grounded in resource-based view theory, the purpose of this qualitative single case study was to explore strategies technology manufacturing leaders use to educate users on how to make optimal cloud technology selection decisions for their organizations. The participants were six executive-level leaders of the strategic sales division of a multinational technology organization based in the western United States who …

Strategies Information Technology Leaders Used In Implementing Remote Work During The Covid-19, Jouliana Kamal Barghouth

Walden Dissertations and Doctoral Studies

With the imposed lockdown in many countries due to the spread of COVID-19, many leaders were forced to adopt online technologies in transitioning employees to remote work. Leaders not adopting online technologies or remote work during a pandemic are highly susceptible to business closure. Grounded in the technology acceptance model, the purpose of this qualitative single case study was to explore strategies information technology (IT) leaders in Kuwait used to successfully transition employees to remote work during the pandemic. The participants were six IT leaders from a single multinational IT organization who contributed to strategy development during the pandemic to …

Mitigation Of Cache Attacks On Cloud Services, Mudassiruddin Mohammed

All Student Theses

Cloud computing is frequently used due to its low cost and flexibility, but it also raises security issues to cloud service providers and customers. Cache attacks are a critical security risk in cloud computing. Cache attacks use weaknesses in cloud servers' cache memory to steal sensitive information, interrupt services, and decrease cloud performance. This study examines the many forms of cache attacks, their possible effects, and known mitigation measures. The study approach includes a review of current methods and their effectiveness in combating cache attack. The report also suggests future research topics for developing more effective and economical methods for …

Utilizing Software Engineering And Cloud Computing Principles To Develop The Revised Self-Report Assessment Of Functional Visual Performance (R-Srafvp) Application, Kirk Hedlich

Culminating Experience Projects

Can principles from software engineering and concepts from cloud computing be applied to and aid in the development of a small project, specifically improving the use of the Revised Self-Report Assessment of Functional Visual Performance (R-SRAFVP)? The target for this project is to create a new application and improve on existing attempts to move the R-SRAFVP assessment from an electronic document format to a web-based application. The new application should provide better ease of use, simplicity in design and understanding for use, and hopefully increased access and adoption by Occupation Therapists who specialize in low vision rehabilitation. The benefits of …

An Acceptable Cloud Computing Model For Public Sectors, Eswar Kumar Devarakonda

Walden Dissertations and Doctoral Studies

Cloud computing enables information technology (IT) leaders to shift from passive business support to active value creators. However, social economic-communication barriers inhibit individual users from strategic use of the cloud. Grounded in the theory of technology acceptance, the purpose of this multiple case study was to explore strategies IT leaders in public sector organizations implement to utilize cloud computing. The participants included nine IT leaders from public sector organizations in Texas, USA. Data were collected using semi-structured interviews, field notes, and publicly available artifacts documents. Data were analyzed using thematic analysis: five themes emerged (a) user-centric and data-driven cloud model; …

A Deep Learning Framework Supporting Model Ownership Protection And Traitor Tracing, Guowen Xu, Hongwei Li, Yuan Zhang, Xiaodong Lin, Robert H. Deng, Xuemin (Sherman) Shen

Research Collection School Of Computing and Information Systems

Cloud-based deep learning (DL) solutions have been widely used in applications ranging from image recognition to speech recognition. Meanwhile, as commercial software and services, such solutions have raised the need for intellectual property rights protection of the underlying DL models. Watermarking is the mainstream of existing solutions to address this concern, by primarily embedding pre-defined secrets in a model's training process. However, existing efforts almost exclusively focus on detecting whether a target model is pirated, without considering traitor tracing. In this paper, we present SecureMark_DL, which enables a model owner to embed a unique fingerprint for every customer within parameters …

Big Data Analytics On Cloud: Challenges, Techniques And Technologies, Aleksander Biberaj, Olimpion Shurdi, Bledar Kazia, Renalda Kushe, Alban Rakipi

UBT International Conference

These days it is known that Big Data Analytics is taking a huge attention from researchers and also from business. We all are witness of the data growth that every institution, company or even individuals store in order to use them in the future. There is a big potential to extract useful data from this Big Data that is stored usually in Cloud because sometimes there is not enough local space to store big amounts of data. There is a huge number of sectors where Big Data can be helpful including economic and business activities, public administration, national security, scientific …

Towards A Cyber-Physical Manufacturing Cloud Through Operable Digital Twins And Virtual Production Lines, Md Rakib Shahriar

Graduate Theses and Dissertations

In last decade, the paradigm of Cyber-Physical Systems (CPS) has integrated industrial manufacturing systems with Cloud Computing technologies for Cloud Manufacturing. Up to 2015, there were many CPS-based manufacturing systems that collected real-time machining data to perform remote monitoring, prognostics and health management, and predictive maintenance. However, these CPS-integrated and network ready machines were not directly connected to the elements of Cloud Manufacturing and required human-in-the-loop. Addressing this gap, we introduced a new paradigm of Cyber-Physical Manufacturing Cloud (CPMC) that bridges a gap between physical machines and virtual space in 2017. CPMC virtualizes machine tools in cloud through web services …

Infusing Raspberry Pi In The Computer Science Curriculum For Enhanced Learning, Fitratullah Khan, Mahmoud K. Quweider, Ala Qubbaj, Emmett Tomai, Lei Xu, Liyu Zhang, Hansheng Lei

Computer Science Faculty Publications and Presentations

With the advent of cloud computing, the Internet of Things (IoT), and mobile computing, CS faculty are continuously revamping the curriculum material to address such burgeoning set of technologies in practical and relatable ways. Raspberry Pi (RPi) devices represent an ideal hardware/software framework that embodies all these technologies through its simple architecture, small form factor (that minimizes the volume and footprint of a desktop computer), and ability to integrate various sensors that network together and connect to the Cloud. Therefore, one of the strategies of Computer Science Department, to enhance depth of learning concepts, has been to infuse Raspberry Pi …

Csci 49378: Introduction To Distributed System And Cloudcomputing: Syllabus, Bonan Liu, Nyc Tech-In-Residence Corps

Open Educational Resources

Syllabus: for CSCI 49378: Introduction to Distributed Systems and Cloud Computing (Spring 2020)

Implementing Cloud-Based Enterprise Resource Planning Solutions In Small And Medium Enterprises, Ali Hamdar

Walden Dissertations and Doctoral Studies

Lacking strategies to implement a cloud-based enterprise resource planning (ERP) solution in small and medium-sized enterprises (SMEs) can lead to a failed implementation. SME owners can improve company performance by integrating company processes by successfully implementing a cloud-based ERP solution. Grounded in the diffusion of innovation theory augmented with business process management design for Six Sigma, the purpose of this qualitative multiple case study was to explore strategies SME owners use to implement cloud-based ERP solutions. The participants consisted of 4 SME owners in Lebanon who successfully implemented a cloud-based ERP solution and improved company performance and growth. Data were …

The Challenges Of Adopting Cloud Computing In Nigerian Government Organizations, Ayodele Adegbenga Bakare

Walden Dissertations and Doctoral Studies

Several technical challenges prevent the adoption of cloud computing by government organizations in Nigeria. Information technology (IT) leaders in the Nigerian government are concerned about this problem because the lack of cloud computing adoption may prevent the Nigerian government from taking advantage of cloud-based information systems to improve its service delivery to citizens and businesses. Grounded in the technology acceptance model, the purpose of this quantitative correlational study was to examine if IT administrators’ perception of data security and perception of fault tolerance can predict their intentions to adopt cloud computing. Data were collected from 79 IT administrators in government …

Developing Cloud Computing Infrastructures In Developing Countries In Asia, Daryoush Charmsaz Moghaddam

Walden Dissertations and Doctoral Studies

Developing Cloud Computing Infrastructures in Developing Countries in Asia

by

Daryoush Charmsaz Moghaddam

MS, Sharif University, 2005

BS, Civil Aviation Higher Education Complex, 1985

Doctoral Study Submitted in Partial Fulfillment

of the Requirements for the Degree of

Doctor of Information Technology

Walden University

March 2020

Virtual Sensor Middleware: A Middleware For Managing Iot Data For The Fog-Cloud Platform, Fadi Almahamid

Electronic Thesis and Dissertation Repository

Internet of Things is a massively growing field where billions of devices are connected to the Internet using different protocols and produce an enormous amount of data. The produced data is consumed and processed by different applications to make operations more efficient. Application development is challenging, especially when applications access sensor data since IoT devices use different communication protocols.

The existing IoT architectures address some of these challenges. This thesis proposes an IoT Middleware that provides applications with the abstraction required of IoT devices while distributing the processing of sensor data to provide a real-time or near real-time response and …

Visualization And Machine Learning Techniques For Nasa’S Em-1 Big Data Problem, Antonio P. Garza Iii, Jose Quinonez, Misael Santana, Nibhrat Lohia

SMU Data Science Review

In this paper, we help NASA solve three Exploration Mission-1 (EM-1) challenges: data storage, computation time, and visualization of complex data. NASA is studying one year of trajectory data to determine available launch opportunities (about 90TBs of data). We improve data storage by introducing a cloud-based solution that provides elasticity and server upgrades. This migration will save $120k in infrastructure costs every four years, and potentially avoid schedule slips. Additionally, it increases computational efficiency by 125%. We further enhance computation via machine learning techniques that use the classic orbital elements to predict valid trajectories. Our machine learning model decreases trajectory …

Machine Learning Pipeline For Exoplanet Classification, George Clayton Sturrock, Brychan Manry, Sohail Rafiqi

SMU Data Science Review

Planet identification has typically been a tasked performed exclusively by teams of astronomers and astrophysicists using methods and tools accessible only to those with years of academic education and training. NASA’s Exoplanet Exploration program has introduced modern satellites capable of capturing a vast array of data regarding celestial objects of interest to assist with researching these objects. The availability of satellite data has opened up the task of planet identification to individuals capable of writing and interpreting machine learning models. In this study, several classification models and datasets are utilized to assign a probability of an observation being an exoplanet. …

Applications Of Fog Computing In Video Streaming, Kyle Smith

Computer Science and Computer Engineering Undergraduate Honors Theses

The purpose of this paper is to show the viability of fog computing in the area of video streaming in vehicles. With the rise of autonomous vehicles, there needs to be a viable entertainment option for users. The cloud fails to address these options due to latency problems experienced during high internet traffic. To improve video streaming speeds, fog computing seems to be the best option. Fog computing brings the cloud closer to the user through the use of intermediary devices known as fog nodes. It does not attempt to replace the cloud but improve the cloud by allowing faster …

Cloud Resource Optimization For Processing Multiple Streams Of Visual Data, Zohar Kapach, Andrew Ulmer, Daniel Merrick, Arshad Alikhan, Yung-Hsiang Lu, Anup Mohan, Ahmed S. Kaseb, George K. Thiruvathukal

George K. Thiruvathukal

Hundreds of millions of network cameras have been installed throughout the world. Each is capable of providing a vast amount of real-time data. Analyzing the massive data generated by these cameras requires significant computational resources and the demands may vary over time. Cloud computing shows the most promise to provide the needed resources on demand. In this article, we investigate how to allocate cloud resources when analyzing real-time data streams from network cameras. A resource manager considers many factors that affect its decisions, including the types of analysis, the number of data streams, and the locations of the cameras. The …

Data-Driven Intelligent Scheduling For Long Running Workloads In Large-Scale Datacenters, Guoyao Xu

Wayne State University Dissertations

Cloud computing is becoming a fundamental facility of society today. Large-scale public or private cloud datacenters spreading millions of servers, as a warehouse-scale computer, are supporting most business of Fortune-500 companies and serving billions of users around the world. Unfortunately, modern industry-wide average datacenter utilization is as low as 6% to 12%. Low utilization not only negatively impacts operational and capital components of cost efficiency, but also becomes the scaling bottleneck due to the limits of electricity delivered by nearby utility. It is critical and challenge to improve multi-resource efficiency for global datacenters.

Additionally, with the great commercial success of …

Strategies For Cloud Services Adoption In Saudi Arabia, Wessam Hussein Abdulghani Mahmoud

Walden Dissertations and Doctoral Studies

The adoption rate of cloud computing is low among business organizations in Saudi Arabia, despite the cost-€saving benefits of using cloud services. The purpose of this multiple case study was to explore the strategies that information technology (IT) leaders in the manufacturing industry in Saudi Arabia used to adopt cloud computing to reduce IT costs. The target population of this study consisted of 5 IT leaders from 5 different manufacturing companies in Saudi Arabia who successfully adopted cloud computing in their companies to reduce IT costs. Rogers's diffusion of innovation theory was the conceptual framework for this research. Data collected …

Cloud Computing Adoption In Afghanistan: A Quantitative Study Based On The Technology Acceptance Model, George T. Nassif

Walden Dissertations and Doctoral Studies

Cloud computing emerged as an alternative to traditional in-house data centers that businesses can leverage to increase the operation agility and employees' productivity. IT solution architects are tasked with presenting to IT managers some analysis reflecting cloud computing adoption critical barriers and challenges. This quantitative correlational study established an enhanced technology acceptance model (TAM) with four external variables: perceived security (PeS), perceived privacy (PeP), perceived connectedness (PeN), and perceived complexity (PeC) as antecedents of perceived usefulness (PU) and perceived ease of use (PEoU) in a cloud computing context. Data collected from 125 participants, who responded to the invitation through an …

Adoption Of Cloud Computing Services In An Illinois-Based Insurance Company, Nekerral Polk

Walden Dissertations and Doctoral Studies

The decision to adopt cloud computing services should involve business units of an insurance company as well as information technology (IT) because cloud computing services are viewed as both a technology offering and business alternative. The purpose of this qualitative exploratory case study was to explore the strategies used by IT architects of an Illinois-based insurance company when adopting cloud computing services. The theory supporting this study was the technology acceptance model. The study's population consisted of IT architects from an Illinois-based insurance company that have used strategies to adopt cloud computing services. This study's data collection included semistructured interviews …

Cloud Resource Optimization For Processing Multiple Streams Of Visual Data, Zohar Kapach, Andrew Ulmer, Daniel Merrick, Arshad Alikhan, Yung-Hsiang Lu, Anup Mohan, Ahmed S. Kaseb, George K. Thiruvathukal

Computer Science: Faculty Publications and Other Works

Hundreds of millions of network cameras have been installed throughout the world. Each is capable of providing a vast amount of real-time data. Analyzing the massive data generated by these cameras requires significant computational resources and the demands may vary over time. Cloud computing shows the most promise to provide the needed resources on demand. In this article, we investigate how to allocate cloud resources when analyzing real-time data streams from network cameras. A resource manager considers many factors that affect its decisions, including the types of analysis, the number of data streams, and the locations of the cameras. The …

Fogfly: A Traffic Light Optimization Solution Based On Fog Computing, Quang Tran Minh, Chanh Minh Tran, Tuan An Le, Binh Thai Nguyen, Triet Minh Tran, Rajesh Krishna Balan

Research Collection School Of Computing and Information Systems

This paper provides a fog-based approach to solving the traffic light optimization problem which utilizes the Adaptive Traffic Signal Control (ATSC) model. ATSC systems demand the ability to strictly reflect real-time traffic state. The proposed fog computing framework, namely FogFly, aligns with this requirement by its natures in location-awareness, low latency and affordability to the changes in traffic conditions. As traffic data is updated timely and processed at fog nodes deployed close to data sources (i.e., vehicles at intersections) traffic light cycles can be optimized efficiently while virtualized resources available at network edges are efficiently utilized. Evaluation results show that …

On The Performance Of Adaptive Bitrate Streaming And Parallel Cloud Applications, Cong Wang

Doctoral Dissertations

As shown in recent studies, video streaming is by far the biggest category of backbone Internet traffic in the US. As a measure to reduce the cost of highly over-provisioned physical infrastructures while remaining the quality of video services, many streaming service providers started to use cloud services, where physical resources can be dynamically allocated based on current demand. In this dissertation, we seek to evaluate and improve the performance for both Adaptive Bitrate (ABR) video streaming and cloud applications. First, we present a set of measurement studies for ABR streaming applications. Using the data from the application, network, and …

Towards Practical Privacy-Preserving Analytics For Iot And Cloud Based Healthcare Systems, Sagar Sharma, Keke Chen, Amit P. Sheth

Kno.e.sis Publications

Modern healthcare systems now rely on advanced computing methods and technologies, such as IoT devices and clouds, to collect and analyze personal health data at unprecedented scale and depth. Patients, doctors, healthcare providers, and researchers depend on analytical models derived from such data sources to remotely monitor patients, early-diagnose diseases, and find personalized treatments and medications. However, without appropriate privacy protection, conducting data analytics becomes a source of privacy nightmare. In this paper, we present the research challenges in developing practical privacy-preserving analytics in healthcare information systems. The study is based on kHealth - a personalized digital healthcare information system …

Security Risk Assessment In Cloud Computing Domains, Amartya Sen

Doctoral Dissertations

"Cyber security is one of the primary concerns persistent across any computing platform. While addressing the apprehensions about security risks, an infinite amount of resources cannot be invested in mitigation measures since organizations operate under budgetary constraints. Therefore the task of performing security risk assessment is imperative to designing optimal mitigation measures, as it provides insight about the strengths and weaknesses of different assets affiliated to a computing platform.

The objective of the research presented in this dissertation is to improve upon existing risk assessment frameworks and guidelines associated to different key assets of Cloud computing domains - infrastructure, applications, …

Aligning Social Media, Mobile, Analytics, And Cloud Computing Technologies And Disaster Response, William Tuley Worthy

Walden Dissertations and Doctoral Studies

After nearly 2 decades of advances in information and communications technologies (ICT) including social media, mobile, analytics, and cloud computing, disaster response agencies in the United States have not been able to improve alignment between ICT-based information and disaster response actions. This grounded theory study explored emergency response ICT managers' understanding of how social media, mobile, analytics, and cloud computing technologies (SMAC) are related to and can inform disaster response strategies. Sociotechnical theory served as the conceptual framework to ground the study. Data were collected from document reviews and semistructured interviews with 9 ICT managers from emergency management agencies in …