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Other Civil and Environmental Engineering

Cloud computing

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Full-Text Articles in Computer Engineering

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 Oct 2016

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

Wes Lloyd

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.


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 Oct 2016

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

Wes Lloyd

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 ...


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 Jun 2014

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 ...


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 Jun 2014

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 ...


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 Jun 2014

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.


Back-End Science Model Integration For Ecological Risk Assessment, Tao Hong, Chancellor Pascale, Jonathan Flaishans, Marcia Snyder, S. Thomas Purucker Jun 2014

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 ...


Tethys: A Software Framework For Web-Based Modeling And Decision Support Applications, Norm Jones, Jim Nelson, Nathan Swain, Scott Christensen, David Tarboton, Pabitra Dash Jun 2014

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 ...


Enabling Water Science At The Cuahsi Water Data Center, Alva Couch, Richard Hooper, Jon Pollak, Marie Martin, Martin Seul Jun 2014

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 ...