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Articles 1 - 8 of 8
Full-Text Articles in Computer Engineering
Performance Optimization Of Big Data Computing Workflows For Batch And Stream Data Processing In Multi-Clouds, Huiyan Cao
Dissertations
Workflow techniques have been widely used as a major computing solution in many science domains. With the rapid deployment of cloud infrastructures around the globe and the economic benefits of cloud-based computing and storage services, an increasing number of scientific workflows have migrated or are in active transition to clouds. As the scale of scientific applications continues to grow, it is now common to deploy various data- and network-intensive computing workflows such as serial computing workflows, MapReduce/Spark-based workflows, and Storm-based stream data processing workflows in multi-cloud environments, where inter-cloud data transfer oftentimes plays a significant role in both workflow performance …
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 …
Energy And Performance-Optimized Scheduling Of Tasks In Distributed Cloud And Edge Computing Systems, Haitao Yuan
Energy And Performance-Optimized Scheduling Of Tasks In Distributed Cloud And Edge Computing Systems, Haitao Yuan
Dissertations
Infrastructure resources in distributed cloud data centers (CDCs) are shared by heterogeneous applications in a high-performance and cost-effective way. Edge computing has emerged as a new paradigm to provide access to computing capacities in end devices. Yet it suffers from such problems as load imbalance, long scheduling time, and limited power of its edge nodes. Therefore, intelligent task scheduling in CDCs and edge nodes is critically important to construct energy-efficient cloud and edge computing systems. Current approaches cannot smartly minimize the total cost of CDCs, maximize their profit and improve quality of service (QoS) of tasks because of aperiodic arrival …
Qos-Aware Scheduling For Data Intensive Workflow, Wan Cong, Cuirong Wang, Wang Cong
Qos-Aware Scheduling For Data Intensive Workflow, Wan Cong, Cuirong Wang, Wang Cong
Journal of System Simulation
Abstract: The development of technology enables people to access resources from different data centers. Resource management and scheduling of applications, such as workflow, that are deployed on the cloud computing environment have already become a hot spot. A QoS-aware scheduling algorithm for data intensive workflow on multiple data center environment was proposed. Scheduling data intensive workflow on multiple data center environment has two characteristics: A large amount of data is distributed in different geographical locations, the process of data migration will consume a large amount of time and bandwidth; secondly, the data centers have different price and resources. Data migration …
Information Collaboration Model Of Cloud Computing Supply Chain Based On Multi-Agent, Wuxue Jiang, Xuanzi Hu, Minxia Liu, Yuqiang Chen
Information Collaboration Model Of Cloud Computing Supply Chain Based On Multi-Agent, Wuxue Jiang, Xuanzi Hu, Minxia Liu, Yuqiang Chen
Journal of System Simulation
Abstract: In order to improve the work efficiency of supply chain in cloud computing and avoid the risks of cloud computing, a cloud-based supply chain information coordination model was proposed. The model has two basic states which are online status and offline status, at online state the cloud computing center is responsible for coordination of the entire supply chain information, and at offline state each node continues to complete the transaction order through the history record and each node information in the cloud data center. Simulation based on Multi-agent shows that the order completion rate in offline status is …
Performance Modeling Of Cryptographic Service System Virtualization Based On Issm, Songhui Guo, Qingbao Li, Sun Lei, Xuerong Gong, Tianchi Yang
Performance Modeling Of Cryptographic Service System Virtualization Based On Issm, Songhui Guo, Qingbao Li, Sun Lei, Xuerong Gong, Tianchi Yang
Journal of System Simulation
Abstract: The complicated architecture of cryptographic service system virtualization raised the difficulty of performance modeling. A performance modeling approach based on ISSMs was proposed. The approach divided the execution process into two stages, host preprocessing and arithmetic-module calculating, and built two sub-models based on queuing theory. On this basis, the effectiveness of this approach was verified. The results show that this method can analyze the impacts on system performance caused by task arrival rates, host and cryptographic card configurations quantitatively, and also be helpful for providing reasonable solutions to deploy virtualized cryptographic service system on cloud computing platforms.
Ml-Medic: A Preliminary Study Of An Interactive Visual Analysis Tool Facilitating Clinical Applications Of Machine Learning For Precision Medicine, Laura Stevens, David Kao, Jennifer Hall, Carsten Görg, Kaitlyn Abdo, Erik Linstead
Ml-Medic: A Preliminary Study Of An Interactive Visual Analysis Tool Facilitating Clinical Applications Of Machine Learning For Precision Medicine, Laura Stevens, David Kao, Jennifer Hall, Carsten Görg, Kaitlyn Abdo, Erik Linstead
Engineering Faculty Articles and Research
Accessible interactive tools that integrate machine learning methods with clinical research and reduce the programming experience required are needed to move science forward. Here, we present Machine Learning for Medical Exploration and Data-Inspired Care (ML-MEDIC), a point-and-click, interactive tool with a visual interface for facilitating machine learning and statistical analyses in clinical research. We deployed ML-MEDIC in the American Heart Association (AHA) Precision Medicine Platform to provide secure internet access and facilitate collaboration. ML-MEDIC’s efficacy for facilitating the adoption of machine learning was evaluated through two case studies in collaboration with clinical domain experts. A domain expert review was also …
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 …