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Articles 1 - 19 of 19
Full-Text Articles in Data Storage Systems
Lecture Notes On Cloud Computing (Ver. Winter 2026), Jun Li
Lecture Notes On Cloud Computing (Ver. Winter 2026), Jun Li
Open Educational Resources
This collection of lecture notes provides a comprehensive technical foundation for modern cloud computing, spanning from physical infrastructure to high-level application patterns. The text explores how warehouse-scale computers and virtualization transformed traditional data centers into flexible, on-demand resource pools characterized by elasticity and a pay-as-you-go economic model. Detailed chapters examine core architectural components, including Kubernetes orchestration, serverless computing (FaaS), and distributed key-value stores like Dynamo. The sources also emphasize the critical nature of fault tolerance, utilizing techniques like erasure coding and replication to manage the statistical inevitability of hardware failure. Security and management are addressed through frameworks like the Shared …
Comparative Performance Analysis Of Cryptographic Workloads Across Cloud Providers: A Multi-Language Study On Faas And Iaas Platforms Dataset, Jeremiah Webb
Doctoral Dissertations and Master's Theses
Cloud computing has become a relatively new paradigm for the delivery of compute resources, with key management services (KMS) playing a crucial role in securely handling cryptographic operations in the cloud. This paper presents the microbenchmark of cloud cryptographic workloads, including SHA HMAC generation, AES encryption/decryption, ECC signature/verification, and RSA encryption/decryption, across Function-as-a-Service (FaaS) and Infrastructure-as-a-Service (IaaS) in conjunction with KMS offerings from Ama- zon Web Services (AWS) and Microsoft Azure to conduct a comparative performance analysis. The methodology involves the AWS Cloud Development Kit (CDK) and the Bicep language to deploy AWS Lambda Functions and Azure Functions, respectively, to …
Batchlens: A Visualization Approach For Analyzing Batch Jobs In Cloud Systems, Shaolun Ruan, Yong Wang, Hailong Jiang, Weijia Xu, Qiang. Guan
Batchlens: A Visualization Approach For Analyzing Batch Jobs In Cloud Systems, Shaolun Ruan, Yong Wang, Hailong Jiang, Weijia Xu, Qiang. Guan
Research Collection School Of Computing and Information Systems
Cloud systems are becoming increasingly powerful and complex. It is highly challenging to identify anomalous execution behaviors and pinpoint problems by examining the overwhelming intermediate results/states in complex application workflows. Domain scientists urgently need a friendly and functional interface to understand the quality of the computing services and the performance of their applications in real time. To meet these needs, we explore data generated by job schedulers and investigate general performance metrics (e.g., utilization of CPU, memory and disk I/O). Specifically, we propose an interactive visual analytics approach, BatchLens, to provide both providers and users of cloud service with an …
Research Framework Of Human Factors Interactions With Technical And Security Factors In Cloud Computing, Hongjiang Xu, Sakthi Mahenthiran
Research Framework Of Human Factors Interactions With Technical And Security Factors In Cloud Computing, Hongjiang Xu, Sakthi Mahenthiran
Scholarship and Professional Work - Business
There are many advantages to adopt cloud computing, however, some important issues need to be addressed, such as cybersecurity, cost-saving, trust, implementation complexity, and cloud provider’s reliability. This study developed a research framework to study the human factors that interact with technical and cybersecurity factors to affect the cloud-computing provider’s performance from the user’s perspective. Research hypotheses were developed and a survey was conducted to test the hypotheses and validate the research framework.
Efficient Fine-Grained Data Sharing Mechanism For Electronic Medical Record Systems With Mobile Devices, Hui Ma, Rui Zhang, Guomin Yang, Zishuai Zong, Kai He, Yuting Xiao
Efficient Fine-Grained Data Sharing Mechanism For Electronic Medical Record Systems With Mobile Devices, Hui Ma, Rui Zhang, Guomin Yang, Zishuai Zong, Kai He, Yuting Xiao
Research Collection School Of Computing and Information Systems
Sharing digital medical records on public cloud storage via mobile devices facilitates patients (doctors) to get (offer) medical treatment of high quality and efficiency. However, challenges such as data privacy protection, flexible data sharing, efficient authority delegation, computation efficiency optimization, are remaining toward achieving practical fine-grained access control in the Electronic Medical Record (EMR) system. In this work, we propose an innovative access control model and a fine-grained data sharing mechanism for EMR, which simultaneously achieves the above-mentioned features and is suitable for resource-constrained mobile devices. In the model, complex computation is outsourced to public cloud servers, leaving almost no …
Load Balancing Of Financial Data Using Machine Learning And Cloud Analytics, Dimple Jaiswal
Load Balancing Of Financial Data Using Machine Learning And Cloud Analytics, Dimple Jaiswal
Masters Theses & Specialist Projects
The rising use of technology for web applications, android applications, digital marketing, and e-application systems for financial investments benefits a large sector of stakeholders and common people. It allows investors to make an appropriate choice for investment and to increase their capital growth. This requires proper research of investment companies, their trends in price and analysis of historical and current information. In addition, prediction of prices makes the process of investment more comfortable and reliable for investors as shares are the most volatile type of investment. To offer this service to multiple users spread across the globe, there are certain …
A Probabilistic Machine Learning Framework For Cloud Resource Selection On The Cloud, Syeduzzaman Khan
A Probabilistic Machine Learning Framework For Cloud Resource Selection On The Cloud, Syeduzzaman Khan
University of the Pacific Theses and Dissertations
The execution of the scientific applications on the Cloud comes with great flexibility, scalability, cost-effectiveness, and substantial computing power. Market-leading Cloud service providers such as Amazon Web service (AWS), Azure, Google Cloud Platform (GCP) offer various general purposes, memory-intensive, and compute-intensive Cloud instances for the execution of scientific applications. The scientific community, especially small research institutions and undergraduate universities, face many hurdles while conducting high-performance computing research in the absence of large dedicated clusters. The Cloud provides a lucrative alternative to dedicated clusters, however a wide range of Cloud computing choices makes the instance selection for the end-users. This thesis …
Privacy-Preserving Mining Of Association Rule On Outsourced Cloud Data From Multiple Parties, Lin Liu, Jinshu Su, Rongmao Chen, Ximeng Liu, Xiaofeng Wang, Shuhui Chen, Ho-Fung Fung Leung
Privacy-Preserving Mining Of Association Rule On Outsourced Cloud Data From Multiple Parties, Lin Liu, Jinshu Su, Rongmao Chen, Ximeng Liu, Xiaofeng Wang, Shuhui Chen, Ho-Fung Fung Leung
Research Collection School Of Computing and Information Systems
It has been widely recognized as a challenge to carry out data analysis and meanwhile preserve its privacy in the cloud. In this work, we mainly focus on a well-known data analysis approach namely association rule mining. We found that the data privacy in this mining approach have not been well considered so far. To address this problem, we propose a scheme for privacy-preserving association rule mining on outsourced cloud data which are uploaded from multiple parties in a twin-cloud architecture. In particular, we mainly consider the scenario where the data owners and miners have different encryption keys that are …
Understanding The Determinants Affecting The Continuance Intention To Use Cloud Computing, Shailja Tripathi Dr.
Understanding The Determinants Affecting The Continuance Intention To Use Cloud Computing, Shailja Tripathi Dr.
Journal of International Technology and Information Management
Cloud computing has been progressively implemented in the organizations. The purpose of the paper is to understand the fundamental factors influencing the senior manager’s continuance intention to use cloud computing in organizations. A conceptual framework was developed by using the Technology Acceptance Model (TAM) as a base theoretical model. A questionnaire was used to collect the data from several companies in IT, manufacturing, finance, pharmaceutical and retail sectors in India. The data analysis was done using structural equation modeling technique. Perceived usefulness and perceived ubiquity are identified as important factors that affect continuance intention to use cloud computing. In addition, …
Blend It Applications And Server, Rebecca Mckinley, Cory Mayer, Tyler Fox, Alex Bartlett, Aly Chapman
Blend It Applications And Server, Rebecca Mckinley, Cory Mayer, Tyler Fox, Alex Bartlett, Aly Chapman
Computer Engineering
No abstract provided.
Data Integrity Verification In Cloud Computing, Katanosh Morovat
Data Integrity Verification In Cloud Computing, Katanosh Morovat
Graduate Theses and Dissertations
Cloud computing is an architecture model which provides computing and storage capacity as a service over the internet. Cloud computing should provide secure services for users and owners of data as well. Cloud computing services are a completely internet-based technology where data are stored and maintained in the data center of a cloud provider. Lack of appropriate control over the data might incur several security issues. As a result, some data stored in the cloud must be protected at all times. These types of data are called sensitive data. Sensitive data is defined as data that must be protected against …
Teaching Cybersecurity Using The Cloud, Khaled Salah, Mohammad Hammoud, Sherali Zeadally
Teaching Cybersecurity Using The Cloud, Khaled Salah, Mohammad Hammoud, Sherali Zeadally
Information Science Faculty Publications
Cloud computing platforms can be highly attractive to conduct course assignments and empower students with valuable and indispensable hands-on experience. In particular, the cloud can offer teaching staff and students (whether local or remote) on-demand, elastic, dedicated, isolated, (virtually) unlimited, and easily configurable virtual machines. As such, employing cloud-based laboratories can have clear advantages over using classical ones, which impose major hindrances against fulfilling pedagogical objectives and do not scale well when the number of students and distant university campuses grows up. We show how the cloud paradigm can be leveraged to teach a cybersecurity course. Specifically, we share our …
The Virtual Machine (Vm) Scaler: An Infrastructure Manager Supporting Environmental Modeling On Iaas Clouds, Wes J. Lloyd, Olaf David, Mazdak Arabi, James C. Ascough Ii, Timothy R. Green, Jack R. Carlson, Ken W. Rojas
The Virtual Machine (Vm) Scaler: An Infrastructure Manager Supporting Environmental Modeling On Iaas Clouds, Wes J. Lloyd, Olaf David, Mazdak Arabi, James C. Ascough Ii, Timothy R. Green, Jack R. Carlson, Ken W. Rojas
International Congress on Environmental Modelling and Software
Infrastructure-as-a-service (IaaS) clouds provide a new medium for deployment of environmental modeling applications. Harnessing advancements in virtualization, IaaS clouds can provide dynamic scalable infrastructure to better support scientific modeling computational demands. Providing scientific modeling “as-a-service” requires dynamic scaling of server infrastructure to adapt to changing user workloads. This paper presents the Virtual Machine (VM) Scaler, an autonomic resource manager for IaaS Clouds. We have developed VM-Scaler, a REST/JSON-based web services application which supports infrastructure provisioning and management to support scientific modeling for the Cloud Services Innovation Platform (CSIP) [Lloyd et al. 2012]. VM-Scaler harnesses the Amazon Elastic Compute Cloud (EC2) …
Modeling-As-A-Service (Maas) Using The Cloud Services Innovation Platform (Csip), Olaf David, Wes Lloyd, Ken Rojas, Mazdak Arabi, Frank Geter, James Ascough, Tim Green, G. Leavesley, Jack Carlson
Modeling-As-A-Service (Maas) Using The Cloud Services Innovation Platform (Csip), Olaf David, Wes Lloyd, Ken Rojas, Mazdak Arabi, Frank Geter, James Ascough, Tim Green, G. Leavesley, Jack Carlson
International Congress on Environmental Modelling and Software
Cloud infrastructures for modelling activities such as data processing, performing environmental simulations, or conducting model calibrations/optimizations provide a cost effective alternative to traditional high performance computing approaches. Cloud-based modelling examples emerged into the more formal notion: "Model-as-a-Service" (MaaS). This paper presents the Cloud Services Innovation Platform (CSIP) as a software framework offering MaaS. It describes both the internal CSIP infrastructure and software architecture that manages cloud resources for typical modelling tasks, and the use of CSIP's "ModelServices API" for a modelling application. CSIP's architecture supports fast and resource aware auto-scaling of computational resources. An example model service is presented: the …
Back-End Science Model Integration For Ecological Risk Assessment, Tao Hong, Chancellor Pascale, Jonathan Flaishans, Marcia Snyder, S. Thomas Purucker
Back-End Science Model Integration For Ecological Risk Assessment, Tao Hong, Chancellor Pascale, Jonathan Flaishans, Marcia Snyder, S. Thomas Purucker
International Congress on Environmental Modelling and Software
The U.S. Environmental Protection Agency (USEPA) relies on a number of ecological risk assessment models that have been developed over 30-plus years of regulating pesticide exposure and risks under Federal Insecticide, Fungicide, and Rodenticide Act (FIFRA) and the Endangered Species Act. Since computing technology have changed dramatically over this time period, constituent legacy models often contain algorithms based on source code with defunct dependencies and/or have been integrated with graphical user interface elements no longer compatible with current operating systems. Model migration to modern web applications creates integration challenges for back-end science model code residing on a server. An example …
Data Provisioning For The Object Modeling System (Oms), Jack R. Carlson, Olaf David, Wes J. Lloyd, George H. Leavesley, Ken W. Rojas, Timothy R. Green, Mazdak Arabi, Lucas Yaege, Hom Kipka
Data Provisioning For The Object Modeling System (Oms), Jack R. Carlson, Olaf David, Wes J. Lloyd, George H. Leavesley, Ken W. Rojas, Timothy R. Green, Mazdak Arabi, Lucas Yaege, Hom Kipka
International Congress on Environmental Modelling and Software
The Object Modelling System (OMS) platform supports initiatives to build or re-factor agro-environmental models and deploy them in different business contexts as model services on cloud computing platforms. Whether traditional desktop, client-server, or emerging cloud deployments, success especially at the enterprise level relies on stable and efficient data provisioning to the models. In this paper we describe recent experience and trends with tools and services deployed to cloud platforms. Also, systematic, sustained data stewardship and alignment with standards organizations impart stability to data provisioning efforts.
Tethys: A Software Framework For Web-Based Modeling And Decision Support Applications, Norm Jones, Jim Nelson, Nathan Swain, Scott Christensen, David Tarboton, Pabitra Dash
Tethys: A Software Framework For Web-Based Modeling And Decision Support Applications, Norm Jones, Jim Nelson, Nathan Swain, Scott Christensen, David Tarboton, Pabitra Dash
International Congress on Environmental Modelling and Software
We have developed a software framework called Tethys to aid in the creation of web-based water resource modeling applications. This suite is a Python-based scripting environment that leverages open source tools for geoprocessing of spatial data, map rendering and visualization, distributed computing, and database management. The system makes it possible to deploy a calibrated, high-resolution watershed or surface water model as a web-based application for decision support. The framework provides data managements, access to computing resources, and pluggable components (e.g. plots, maps and user controls) that enable rapid development of modeling applications. We have used the system to develop prototype …
Enabling Water Science At The Cuahsi Water Data Center, Alva Couch, Richard Hooper, Jon Pollak, Marie Martin, Martin Seul
Enabling Water Science At The Cuahsi Water Data Center, Alva Couch, Richard Hooper, Jon Pollak, Marie Martin, Martin Seul
International Congress on Environmental Modelling and Software
The CUAHSI Water Data Center (WDC) is a community-governed, multi-disciplinary data center focused upon the needs of water-related science in all academic disciplines. The WDC build upon the successes of the 10-year effort to develop the CUAHSI Hydrologic Information System (HIS), and looks beyond HIS toward providing next-generation water data services. In partnership with the National Science Foundation, the WDC seeks to set the standard for data publication, persistence, and reliability, by providing formal user support services, using cloud-based abstractions and services, building new and accessible user interfaces to data, and establishing and sustaining data curation processes centered around optimizing …
Data Management In Cloud Environments: Nosql And Newsql Data Stores, Katarina Grolinger, Wilson A. Higashino, Abhinav Tiwari, Miriam Am Capretz
Data Management In Cloud Environments: Nosql And Newsql Data Stores, Katarina Grolinger, Wilson A. Higashino, Abhinav Tiwari, Miriam Am Capretz
Electrical and Computer Engineering Publications
: Advances in Web technology and the proliferation of mobile devices and sensors connected to the Internet have resulted in immense processing and storage requirements. Cloud computing has emerged as a paradigm that promises to meet these requirements. This work focuses on the storage aspect of cloud computing, specifically on data management in cloud environments. Traditional relational databases were designed in a different hardware and software era and are facing challenges in meeting the performance and scale requirements of Big Data. NoSQL and NewSQL data stores present themselves as alternatives that can handle huge volume of data. Because of the …