Computer Sciences Commons^™

Workflow Critical Path: A Data-Oriented Path Metric For Holistic Hpc Workflows, Daniel D. Nguyen

Dissertations and Theses

Optimizing scientific application performance in HPC environments is a complicated task which has motivated the development of many performance analysis tools over the past decades. These tools were designed to analyze the performance of a single parallel code using common approaches such as message passing (MPI), multithreading (OpenMP), acceleration (CUDA), or a hybrid approach. However, current trends in HPC such as the push to exascale, convergence with Big Data, and growing complexity of HPC applications and scientific workflows, have created gaps that these performance tools do not cover, particularly involving end-to-end data movement through an end-to-end HPC workflow comprising multiple …

Balancing Security, Performance And Deployability In Encrypted Search, David Joel Pouliot

Dissertations and Theses

Encryption is an important tool for protecting data, especially data stored in the cloud. However, standard encryption techniques prevent efficient search. Searchable encryption attempts to solve this issue, protecting the data while still providing search functionality. Retaining the ability to search comes at a cost of security, performance and/or utility.

An important practical aspect of utility is compatibility with legacy systems. Unfortunately, the efficient searchable encryption constructions that are compatible with these systems have been proven vulnerable to attack, even against weaker adversary models.

The goal of this work is to address this security problem inherent with efficient, legacy compatible …

Privacy-Preserving Data Processing With Flexible Access Control, Wenxiu Ding, Zheng Yan, Robert H. Deng

Research Collection School Of Computing and Information Systems

Cloud computing provides an efficient and convenient platform for cloud users to store, process and control their data. Cloud overcomes the bottlenecks of resource-constrained user devices and greatly releases their storage and computing burdens. However, due to the lack of full trust in cloud service providers, the cloud users generally prefer to outsource their sensitive data in an encrypted form, which, however, seriously complicates data processing, analysis, as well as access control. Homomorphic encryption (HE) as a single key system cannot flexibly control data sharing and access after encrypted data processing. How to realize various computations over encrypted data in …

Lambda Edge: A Lambda Computing Platform For Edge Computing, Dung Nguyen

Theses and Dissertations

Edge computing is a solution to the mobile computation offloading problem. Previous works show that virtual machines can be the computation units in edge computing. However, virtual machine-based methods are usually associated with large overheads and long latencies. In this thesis, we explore the possibility of using Docker containers instead of virtual machines in edge computing enabled by lambda architecture. We propose an edge computing platform, called Lambda Edge, which can be used to build edge computing applications and pave the way for further research on lambda-based edge computing. We also provide a sample application built upon the platform. We …

Scalable, Adaptable And Fast Estimation Of Transient Downtime In Virtual Infrastructures Using Convex Decomposition And Sample Path Randomization, Zhiling Guo, Jin Li, Ram Ramesh

Research Collection School Of Computing and Information Systems

Network function virtualization enables efficient cloud-resource planning by virtualizing network services and applications into software running on commodity servers. A cloud-service provider needs to manage and ensure service availability of a network of concurrent virtualized network functions (VNFs). The downtime distribution of a network of VNFs can be estimated using sample-path randomization on the underlying birth–death process. An integrated modeling approach for this purpose is limited by its scalability and computational load because of the high dimensionality of the integrated birth–death process. We propose a generalized convex decomposition of the integrated birth-death process, which transforms the high-dimensional multi-VNF process into …

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 …

Small-To-Medium-Size Enterprise Managers’ Experiences With Cloud Computing, Anthony Effiong

Walden Dissertations and Doctoral Studies

Historically, managers of small- and medium-sized enterprises (SMEs) have had concerns regarding cloud computing and cybersecurity. Their resistance to using cloud computing has influenced their ability to do business effectively and to compete with businesses that use cloud computing. The purposes of this descriptive phenomenological study were to explore the lived experiences and perceptions of SME managers that might influence their decisions to adopt cloud computing. Watson’s concept of resistance to change and Davis, Bagozzi, and Warhaw’s technology acceptance model were the conceptual frameworks that guided this qualitative study. Data collection consisted of conducting 16 semi-structured interviews with open-ended questions …

Exploring Trust In Cloud Computing For A Governmental Organization In Ethiopia: A Case Study, Estifanos Abebe Seyoum

Walden Dissertations and Doctoral Studies

Organizations face a rapidly changing environment that forces them to seek high computing power. The problem was how to overcome factors that cause managers at governmental organizations in Ethiopia to be reluctant to trust cloud computing, while some managers overcame this lack of trust. The purpose of this qualitative, single case study was to provide a deeper understanding of how a governmental organization in Ethiopia overcame the factors that adversely influenced managers of other organizations to the extent that they distrusted and decided against adopting cloud computing. The population for this study was comprised of 12 managers from a governmental …

Scalable And Secure Big Data Iot System Based On Multifactor Authentication And Lightweight Cryptography, Saleh Atiewi, Amer Al-Rahayfeh, Muder Almiani, Salman Yussof, Omar Alfandi, Ahed Abugabah, Yaser Jararweh

All Works

© 2013 IEEE. Organizations share an evolving interest in adopting a cloud computing approach for Internet of Things (IoT) applications. Integrating IoT devices and cloud computing technology is considered as an effective approach to storing and managing the enormous amount of data generated by various devices. However, big data security of these organizations presents a challenge in the IoT-cloud architecture. To overcome security issues, we propose a cloud-enabled IoT environment supported by multifactor authentication and lightweight cryptography encryption schemes to protect big data system. The proposed hybrid cloud environment is aimed at protecting organizations' data in a highly secure manner. …

How Location-Aware Access Control Affects User Privacy And Security In Cloud Computing Systems, Wen Zeng, Reem Bashir, Trevor Wood, Francois Siewe, Helge Janicke, Isabel Wagner

Research outputs 2014 to 2021

The use of cloud computing (CC) is rapidly increasing due to the demand for internet services and communications. The large number of services and data stored in the cloud creates security risks due to the dynamic movement of data, connected devices and users between various cloud environments. In this study, we will develop an innovative prototype for location-aware access control and data privacy for CC systems. We will apply location-aware access control policies to role-based access control of Cloud Foundry, and then analyze the impact on user privacy after implementing these policies. This innovation can be used to address the …

Ai Techniques For Covid-19, Adedoyin Ahmed Hussain, Ouns Bouachir, Fadi Al-Turjman, Moayad Aloqaily

All Works

© 2013 IEEE. Artificial Intelligence (AI) intent is to facilitate human limits. It is getting a standpoint on human administrations, filled by the growing availability of restorative clinical data and quick progression of insightful strategies. Motivated by the need to highlight the need for employing AI in battling the COVID-19 Crisis, this survey summarizes the current state of AI applications in clinical administrations while battling COVID-19. Furthermore, we highlight the application of Big Data while understanding this virus. We also overview various intelligence techniques and methods that can be applied to various types of medical information-based pandemic. We classify the …

Server-Aided Revocable Attribute-Based Encryption For Cloud Computing Services, Hui Cui, Tsz Hon Yuen, Robert H. Deng, Guilin Wang

Research Collection School Of Computing and Information Systems

Attribute-based encryption (ABE) has been regarded as a promising solution in cloud computing services to enable scalable access control without compromising the security. Despite of the advantages, efficient user revocation has been a challenge in ABE. One suggestion for user revocation is using the binary tree in the key generation phase of an ABE scheme, which enables a trusted key generation center to periodically distribute the key update information to all nonrevoked users over a public channel. This revocation approach reduces the size of key updates from linear to logarithmic in the number of users. But it requires each user …

Pgas: Privacy-Preserving Graph Encryption For Accurate Constrained Shortest Distance Queries, Can Zhang, Liehuang Zhu, Kashif Sharif, Chuan Zhang, Ximeng Liu

Research Collection School Of Computing and Information Systems

The constrained shortest distance (CSD) query is used to determine the shortest distance between two vertices of a graph while ensuring that the total cost remains lower than a given threshold. The virtually unlimited storage and processing capabilities of cloud computing have enabled the graph owners to outsource their graph data to cloud servers. However, it may introduce privacy challenges that are difficult to address. In recent years, some relevant schemes that support the shortest distance query on the encrypted graph have been proposed. Unfortunately, some of them have unacceptable query accuracy, and some of them leak sensitive information that …

A Cloud Service Composition Optimization Based On Hnn, Huili Zhang, Zhihe Li

Journal of System Simulation

Abstract: With the rapid development of Cloud service application, how to effectively optimize the composition of Cloud services on cloud platform and improve the overall performance of cloud platform system have become an urgent research issue. In order to improve the efficiency of Cloud services, a combined optimization model based on Hopfield neural network is proposed. The problem of Cloud services is modeled. The problem is expressed as Hopfield Neural Network energy model for optimization, and a PSO group algorithm with Cauchy disturbance is designed to improve the Hopfield model. The experimental comparison shows that the method can improve …

Modeling And Simulation Of Complex Equipment Health Management System Based On Cloud Computing, Tianrui Zhang, Chuansheng Qu, Baoku Wu, Jianan Xu

Journal of System Simulation

Abstract: For complex equipment operation safely, the health management problems of complex equipment life cycle is analyzed. In order to realize remote service, complex equipment health management mode based on cloud computing is proposed. Aiming at the accuracy problem in the process of extracting and recognizing complex equipment characteristic data, the feature knowledge acquisition method based on ontology is researched, and the expression and acquisition algorithm of state characteristic knowledge is proposed. A task sequencing algorithm faults based on fuzzy comprehensive evaluation method is proposed, an appropriate task assignment model is selected for scheduling health management technicians. …

Optimal Management Of Virtual Infrastructures Under Flexible Cloud Service Agreements, Zhiling Guo, Jin Li, Ram Ramesh

Research Collection School Of Computing and Information Systems

A cloud service agreement entails the provisioning of a required set of virtual infrastructure resources at a specified level of availability to a client. The agreement also lays out the price charged to the client and a penalty to the provider when the assured availability is not met. The availability assurance involves backup resource provisioning, and the provider needs to allocate backups cost-effectively by balancing the resource-provisioning costs with the potential penalty costs. We develop stochastic dynamic optimization models of the backup resource-provisioning problem, leading to cost-effective resource-management policies in different practical settings. We present two sets of dynamic provisioning …

Hiding In Plain Sight? The Impact Of Face Recognition Services On Privacy, James Richard Ortega

Computer Science and Engineering Theses - Archive

The public at large is increasingly concerned with privacy online. While the focus is on the data privately collected by platforms, there are also privacy concerns in the realm of public data. Seemingly innocuous information shared in public, on online platforms, can be pieced together to detrimentally affect one's privacy in unexpected ways. On YouTube there exists a rich public dataset for adversaries to analyze for the purposes of breaching privacy; particularly due to the intersection of location and facial data. The goal of this work is to characterize the privacy risks that exists on YouTube, and explore the viability …

Fog Computing Enabling Industrial Internet Of Things: State-Of-The-Art And Research Challenges, Rabeea Basir, Saad Qaisar, Mudassar Ali, Monther Aldwairi, Muhammad Ikram Ashraf, Aamir Mahmood, Mikael Gidlund

All Works

© 2019 by the authors. Licensee MDPI, Basel, Switzerland. Industry is going through a transformation phase, enabling automation and data exchange in manufacturing technologies and processes, and this transformation is called Industry 4.0. Industrial Internet-of-Things (IIoT) applications require real-time processing, near-by storage, ultra-low latency, reliability and high data rate, all of which can be satisfied by fog computing architecture. With smart devices expected to grow exponentially, the need for an optimized fog computing architecture and protocols is crucial. Therein, efficient, intelligent and decentralized solutions are required to ensure real-time connectivity, reliability and green communication. In this paper, we provide a …

Cloud Computing Architecture For Elearning Systems In Secondary Schools In Tanzania, Kennedy F. Mwakisole, Mussa M. Kissaka Dr, Joel S. Mtebe Phd

The African Journal of Information Systems

In recent years, schools have been investing heavily on information and communications technology (ICT) infrastructure to implement eLearning systems to enhance the quality of education in secondary schools in Tanzania. The majority of these systems are implemented using a traditional web-based eLearning approach on school premises which is costly and limits usage due to lack of scalability and flexibility. Consequently, many schools have started adopting cloud computing as a solution. However, this adaption depends on well-defined cloud eLearning architecture. This study proposed cloud architecture for implementing an eLearning system in secondary schools in Tanzania by adopting various layers proposed in …

Cloud Computing (Ksu), Yong Shi, Dan Lo, Selena He, Mingon Kang, Sarah North

Computer Science and Information Technology Grants Collections

This Grants Collection for Cloud Computing was created under a Round Twelve ALG Textbook Transformation Grant.

Affordable Learning Georgia Grants Collections are intended to provide faculty with the frameworks to quickly implement or revise the same materials as a Textbook Transformation Grants team, along with the aims and lessons learned from project teams during the implementation process.

Documents are in .pdf format, with a separate .docx (Word) version available for download. Each collection contains the following materials:

• Linked Syllabus
• Initial Proposal
• Final Report

Lightweight Fine-Grained Search Over Encrypted Data In Fog Computing, Yinbin Miao, Jianfeng Ma, Ximeng Liu, Jian Weng, Hongwei Li, Hui Li

Research Collection School Of Computing and Information Systems

Fog computing, as an extension of cloud computing, outsources the encrypted sensitive data to multiple fog nodes on the edge of Internet of Things (IoT) to decrease latency and network congestion. However, the existing ciphertext retrieval schemes rarely focus on the fog computing environment and most of them still impose high computational and storage overhead on resource-limited end users. In this paper, we first present a Lightweight Fine-Grained ciphertexts Search (LFGS) system in fog computing by extending Ciphertext-Policy Attribute-Based Encryption (CP-ABE) and Searchable Encryption (SE) technologies, which can achieve fine-grained access control and keyword search simultaneously. The LFGS can shift …

Design And Experimental Evaluation Of Deepmarket: An Edge Computing Marketplace With Distributed Tensorflow Execution Capability, Soyoung Kim

Dissertations and Theses

There is a rise in demand among machine learning researchers for powerful computational resources to train complex machine learning models, e.g., deep learning models. In order to train these models in a reasonable amount of time, the training is often distributed among multiple machines; yet paying for such machines (either through renting them on cloud data centers or building a local infrastructure) is costly. DeepMarket attempts to reduce these costs by creating a marketplace that integrates multiple computational resources over a distributed TensorFlow framework. Instead of requiring users to rent expensive GPU/CPUs from a third-party cloud provider, DeepMarket allows users …

Practical And Effective Sandboxing For Linux Containers, Zhiyuan Wan, David Lo, Xin Xia, Liang Cai

Research Collection School Of Computing and Information Systems

A container is a group of processes isolated from other groups via distinct kernel namespaces and resource allocation quota. Attacks against containers often leverage kernel exploits through the system call interface. In this paper, we present an approach that mines sandboxes and enables fine-grained sandbox enforcement for containers. We first explore the behavior of a container by running test cases and monitor the accessed system calls including types and arguments during testing. We then characterize the types and arguments of system call invocations and translate them into sandbox rules for the container. The mined sandbox restricts the container’s access to …

A Scalable Approach To Joint Cyber Insurance And Security-As-A-Service Provisioning In Cloud Computing, Jonathan David Chase, Dusit Niyato, Ping Wang, Sivadon Chaisiri, Ryan K. L. Ko

Research Collection School Of Computing and Information Systems

As computing services are increasingly cloud-based, corporations are investing in cloud-based security measures. The Security-as-a-Service (SECaaS) paradigm allows customers to outsource security to the cloud, through the payment of a subscription fee. However, no security system is bulletproof, and even one successful attack can result in the loss of data and revenue worth millions of dollars. To guard against this eventuality, customers may also purchase cyber insurance to receive recompense in the case of loss. To achieve cost effectiveness, it is necessary to balance provisioning of security and insurance, even when future costs and risks are uncertain. To this end, …

Predictive Analysis For Cloud Infrastructure Metrics, Paridhi Agrawal

Master's Projects

In a cloud computing environment, enterprises have the flexibility to request resources according to their application demands. This elastic feature of cloud computing makes it an attractive option for enterprises to host their applications on the cloud. Cloud providers usually exploit this elasticity by auto-scaling the application resources for quality assurance. However, there is a setup-time delay that may take minutes between the demand for a new resource and it being prepared for utilization. This causes the static resource provisioning techniques, which request allocation of a new resource only when the application breaches a specific threshold, to be slow and …

Designing Computational Biology Workflows With Perl - Part 1 & 2, Esma Yildirim

Open Educational Resources

This manual guides the instructor to combine the partial files of the virtual machine image and construct sequencer.ova file. It is accompanied by the partial files of the virtual machine image.

Implementation And Analysis Of Xcache On Southwest Tier 2 Cloud Cluster For Large Hadron Collider Atlas Experiment, Priyam Banerjee

Computer Science and Engineering Theses - Archive

The ATLAS Experiment is one of the four major particle-detector experiments at the Large Hadron Collider at CERN (birthplace of the World Wide Web). The ATLAS was one of the LHC experiments that successfully demonstrated the discovery of the Higgs-Boson in July 2012. At the end of 2018, CERN data archiving on tape-based drives reached 330 PB. Through the Worldwide LHC Computing Grid (WLCG), a distributed computing infrastructure, the calibrated data out of the particle accelerator is split in chunks and distributed all around the world for analysis. The WLCG runs more than two million jobs per day. At peak …

Building Consumer Trust In The Cloud: An Experimental Analysis Of The Cloud Trust Label Approach, Lisa Van Der Werff, Grace Fox, Ieva Masevic, Vincent C. Emeakaroha, John P. Morrison, Theo Lynn

Department of Computer Science Publications

The lack of transparency surrounding cloud service provision makes it difficult for consumers to make knowledge based purchasing decisions. As a result, consumer trust has become a major impediment to cloud computing adoption. Cloud Trust Labels represent a means of communicating relevant service and security information to potential customers on the cloud service provided, thereby facilitating informed decision making. This research investigates the potential of a Cloud Trust Label system to overcome the trust barrier. Specifically, it examines the impact of a Cloud Trust Label on consumer perceptions of a service and cloud service provider trustworthiness and trust in the …

Zhvillimi I Një Web Aplikacioni Bazuar Në Arkitekturën Serverless, Freskim Aliu

Theses and Dissertations

No abstract provided.

Cloud Job Scheduling Model Based On Improved Plant Growth Algorithm, Li Qiang, Xiaofeng Liu

Journal of System Simulation

Abstract: The performance of cloud job scheduling algorithm has a great importance to the whole cloud system. The key factors that affect cloud operation scheduling are found out, and a resource constraint model is established. The existing simulation plant growth algorithm is improved based on the Logistic model of plant growth law, so that the plant growth way was made to change according to the energy power. The comparison of four different plant models was carried out and their different features were analyzed. Compared with 6 typical cloud job scheduling algorithms, it is concluded that the improved simulation plant growth …