Faculty & Staff Publications

Permanent URI for this collectionhttps://hdl.handle.net/1773/53080

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Model-As-A-Service (MaaS) Using the Cloud Services Innovation Platform (CSIP)
(iEMSs 2014 International Congress on Environmental Modeling and Software - Bold Visions for Environmental Modelling, Seventh Biennial Meeting, 6/1/2014) David, Olaf; Lloyd, Wesley James; Rojas, Ken W.; Arabi, Mazdak; Geter, F.; Ascough II, James C.; Green, Timothy R.; Leavesley, George H.; Carlson, Jack R.
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 m ore 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 USDA hydrograph model EFH2 used in the desktop - based 'engineering field tools' is deployed as a CSIP service. This and other MaaS CSIP examples benefit from the use of cloud resources to enable straightforward scalable model deployment into cloud environments.
Performance Modeling to Support Multi-Tier Application Deployment to Infrastructure-As-A-Service Clouds
(Utility and Cloud Computing (UCC), 2012 IEEE Fifth International Conference On, 11/1/2012) Lloyd, Wesley James; Pallickara, Shrideep; David, Olaf; Lyon, Jim; Arabi, Mazdak; Rojas, Ken W.
Infrastructure-as-a-service (IaaS) clouds support migration of multi-tier applications through virtualization of diverse application stack(s) of components which may require various operating systems and environments. To maximize performance of applications deployed to IaaS clouds while minimizing deployment costs, it is necessary to create virtual machine images to host application components with consideration for component dependencies that may affect load balancing of physical resources of VM hosts including CPU time, disk and network bandwidth. This paper presents results of an investigation utilizing physical machine (PM) and virtual machine (VM) resource utilization statistics to build performance models to predict application performance and rank performance of application component deployment configurations deployed across VMs. Our objective was to predict which component compositions provide best performance while requiring the fewest number of VMs. Eighteen individual resource utilization statistics were investigated for use as independent variables to predict service execution time using four different modeling approaches. Overall CPU time was the strongest predictor of execution time. The strength of individual predictors varied with respect to the resource utilization profiles of the applications. CPU statistics including idle time and number of context switches were good predictors when the test application was more disk I/O bound, while disk I/O statistics were better predictors when the application was more CPU bound. All performance models built were effective at determining the best performing service composition deployments validating the utility of our approach.
Short and Long Term Energy Storage for Enhanced Resilience of Electric Infrastructures Storage of Compressed Hydrogen and Oxygen Gasses Derived From Electrolysis to Provide Grid Connected Mechanical and Electrochemical Electrical Power Generation on Demand
(2014 5th International Renewable Energy Congress (IREC), 3/1/2013) Grant, DC
Energy storage based upon converting electricity from water to hydrogen gas provides a solution to the problem of intermittency in renewable energy systems. These benefits are not specific to isolated solar and wind energy production but can also be derived as a complement to load and demand variations on the fully integrated electrical grid. The main components of this system are electrolytic cells, which use electricity to generate hydrogen and oxygen from water, compressed gas hydrogen and oxygen storage tanks and fuel cells, which recombine hydrogen with oxygen to generate electricity. At times of excess energy availability, electrolytic cells are used as a controllable load by which the excess energy is converted into hydrogen and oxygen gas. When there is insufficient energy to meet demands, the fuel cell is used to recombine hydrogen and oxygen into water and create electricity. Water storage and compressed gasses can be used to further tune the load. Water can be pumped from one reservoir to another to create artificial demand, and can be allowed to flow by gravitational power to create electricity on demand. Compressed gasses can similarly be managed to create load or increase generation capacity at will. These complements are key to effectively managing electrolytic cell arrays for maximum potential, but also provide for very high versatility and resilience of the system, which can allow operators to micro-manage electrical supplies and demands. This work examines the technical details of such systems and extracts some of the lessons learned from more than fifty years of related research, prototyping and implementations.
The Virtual Machine (VM) Scaler: An Infrastructure Manager Supporting Environmental Modeling on IaaS Clouds
(iEMSs 2014 International Congress on Environmental Modeling and Software - Bold Visions for Environmental Modelling, Seventh Biennial Meeting, 6/1/2014) Lloyd, Wesley James; David, Olaf; Arabi, Mazdak; Ascough II, James C.; Green, Timothy R.; Carlson, Jack R.; Rojas, Ken W.
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) application programming interface to support model- service scalability, cloud management, and infrastructure configuration for supporting modeling workloads. VM-Scaler provides "cloud control" while abstracting the underlying IaaS cloud from the end user. VM-Scaler is extensible to support any EC2 compatible cloud and currently supports the Amazon public cloud and Eucalyptus private clouds versions 3.1 and 3.3. VM-Scaler provides a platform to improve scientific model deployment by supporting experimentation with: hot spot detection schemes, VM management and placement approaches, and model job scheduling/proxy services.
The Cloud Services Innovation Platform-Enabling Service-Based Environmental Modelling Using Infrastructure-As-A-Service Cloud Computing
(Meeting Proceedings, 1/1/2012) Lloyd, Wesley James; David, Olaf; Ascough II, James C.; Green, T.R.; Carlson, Jack R.; Lyon, Jim; Rojas, Ken W.
Service oriented architectures allow modelling engines to be hosted over the Internet abstracting physical hardware configuration and software deployments from model users. Many existing environmental models are deployed as desktop applications running on user's personal computers (PCs). Migration to service - based modelling centralizes the modelling functions to service hosts on the Internet . Users no longer require high-end PCs to run models and model updates encapsulating science advances can be disseminated more rapidly by hosting the modelling functions centrally via an Internet host instead of requiring software updates to user's PCs . In this paper we present the Cloud Services Innovation Platform (CSIP), an Infrastructure -as -a -Service cloud application architecture , used to prototype development of distributed and scalable environmental modelling services. CSIP aims to provide modelling as a service to support both interactive (synchronous) and batch (asynchronous) modelling. CSIP enables c loud-based computing resources to be harnessed for both new and existing environmental models supporting the disaggregation of work into subtasks which execute in parallel using a scalable number of virtual machines. This paper presents CSIP 's implementation using the RUSLE2 model as a prototype model. RUSLE2 model service benchmarks are presented to demonstrate performance gains from using cloud resources. We also provide benchmarks for virtualization overhead observed using popular virtual machine hypervisors and demonstrate how application profile characteristics significantly impact performance when virtualized.
Migration of Multi-Tier Applications to Infrastructure-As-A-Service Clouds: An Investigation Using Kernel-Based Virtual Machines
(2011 IEEE/ACM 12th International Conference on Grid Computing, 10 % overhead for the processor bound application. Understanding an application's profile was found to be important for optimal IaaS -based cloud migration and scaling.) Lloyd, Wesley James; Pallickara, Shrideep; David, Olaf; Lyon, Jim; Arabi, Mazdak; Rojas, Ken W.
To investigate challenges of multi -tier application migration to Infrastructure -as-a- Service (IaaS) clouds we performed an experimental investigation by deploying a processor bound and input -output bound variant of the RUSLE2 erosion model to an IaaS base d private cloud. Scaling the applications to achieve optimal system throughput is complex and involves much more than simply increasing the number of allotted virtual machines (VMs). While scaling the application variants a series of bottlenecks were encountered unique to an application's processing, I/O, and memory requirements, herein referred to as an application's profile. To investigate the impact of provisioning variation for hosting multi -tier applications we tested four schemes of VM deployments across the physical nodes of our cloud. Performance degradation was more pronounced when multiple I/O or CPU resource intensive application components were co -located on the same physical hardware. We investigated the virtualization overhead incurred using Kernel -based virtual machines (KVM) by deploying our application variants to both physical and virtual machines. Overhead varied based on the unique characteristics of each application's profile. We observed
Service Isolation vs. Consolidation: Implications for Iaas Cloud Application Deployment
(Cloud Engineering (IC2E), 2013 IEEE International Conference On) Lloyd, Wesley James; Pallickara, Shrideep; David, Olaf; Lyon, Jim; Arabi, Mazdak; Rojas, Ken W.
Service isolation, achieved by deploying components of multi -tier applications using separate virtual machines (VMs), is a common 'best' practice. Various advantages cited include simpler deployment architectures, easier resource scalability for supporting dynamic application throughput requirements, and support for component-level fault tolerance . This paper presents results from an empirical study which investigates the performance implications of component placement for deployments of multi -tier applications to Infrastructure-as-a- Service (IaaS) clouds. Relationship s between performance and resource utilization (CPU, disk, network) are investigated to better understand the implications which result from how applications are deployed. All possible deployments for two variants of a multi -tier application were tested, one computationally bound by the model, the other bound by a geospatial database. The best performing deployments required as few as 2 VMs, half the number required for service isolation, demonstrating potential cost savings with service consolidation. Resource use (CPU time, disk I/O, and network I/O) varied based on component placement and VM memory allocation. Using separate VMs to host each application component resulted in performance overhead of
Data Provisioning for the Object Modeling System (OMS)
(iEMSs 2014 International Congress on Environmental Modeling and Software - Bold Visions for Environmental Modelling, Seventh Biennial Meeting, 6/1/2014) Carlson, Jack, R.; David, Olaf; Lloyd, Wesley James; Leavesley, George H.; Rojas, Ken W.; Green, Timothy R.; Arabi, Mazdak; Yaege, Lucas; Kipka, Hom
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 to supply data for model inputs. Solutions range from simple pre - processing tools to data services deployed to cloud platforms. Also, systematic, sustained data stewardship and alignment with standards organizations impart stability to data provisioning efforts.
Dynamic Scaling for Service Oriented Applications: Implications of Virtual Machine Placement on IaaS Clouds
(Cloud Engineering (IC2E), 2014 IEEE International Conference On, 3/1/2014) Lloyd, Wesley James; Pallickara, Shrideep; David, Olaf; Arabi, Mazdak; Rojas, Ken W.
Abstraction of physical hardware using infrastructure-as-a-service (IaaS) clouds leads to the simplistic view that resources are homogeneous and that infinite scaling is possible with linear increases in performance. Support for autonomic scaling of multi-tier service oriented applications requires determination of when, what, and where to scale. 'When' is addressed by hotspot detection schemes using techniques including performance modeling and time series analysis. 'What' relates to determining the quantity and size of new resources to provision. 'Where' involves identification of the best location(s) to provision new resources. In this paper we investigate primarily 'where' new infrastructure should be provisioned, and secondly 'what' the infrastructure should be. Dynamic scaling of infrastructure for service oriented applications requires rapid response to changes in demand to meet application quality-of-service requirements. We investigate the performance and resource cost implications of VM placement when dynamically scaling server infrastructure of service oriented applications . We evaluate dynamic scaling in the context of providing modeling-as-a-service for two environmental science models.
Environmental Modeling Framework Invasiveness: Analysis and Implications
(Environmental Modelling & Software, 3/28/2011) Lloyd, Wesley James; David, Olaf; Ascough II, James C.; Rojas, Ken W.; Carlson, Jack R.; Leavesley, George H.; Krause, Peter; Green, Timothy R.; Ahuja, Lajpat R.
Environmental modeling frameworks support scientific model development by providing an Application Programming Interface (API) which model developers use to implement models. This paper presents results of an investigation on the framework invasiveness of environmental modeling frameworks. Invasiveness is defined as the quantity of dependencies between model code and the modeling framework. This research investigates relationships between invasiveness and the quality of modeling code. Additionally, we investigate the relationship between invasiveness and two common framework designs (lightweight vs. heavyweight). Five metrics to measure framework invasiveness were proposed and applied to measure invasiveness between model and framework code of several implementations of Thornthwaite and the Precipitation-Runoff Modeling System (PRMS), two hydrological models. Framework invasiveness measurements were compared with existing software metrics including size (lines of code), cyclomatic complexity, and object-oriented coupling with generally positive correlations being found. We found that models with lower framework invasiveness tended to be smaller, less complex, and have lower coupling. In addition, the lightweight framework implementations of the Thornthwaite and PRMS models were less invasive than the heavyweight framework model implementations. Our initial results suggest that framework invasiveness is undesirable for model code quality and that lightweight frameworks may help reduce invasiveness.
Building a Computer Network Immune System
(Security Congress 2015, 9/28/2015) Grant, DC
An Exploratory Investigation on the Invasiveness of Environmental Modeling Frameworks
(The 18th World IMACS Congress and MODSIM09 International Congress on Modelling and Simulation, 1/1/2009) Lloyd, Wesley James; David, Olaf; Ascough II, James C.; Rojas, Ken W.; Carlson, Jack R.; Leavesley, George H.; Krause, Peter; Green, Timothy R.; Ahuja, Lajpat R.
Environmental modeling frameworks provide an array of useful features that model developers can harness when implementing models. Each framework differs in how it provides features to a model developer via its Application Programming Interface (API). Environmental modelers harness framework features by calling and interfacing with the framework API. As modelers write model code, they make framework-specific function calls and use framework specific data types for achieving the functionality of the model. As a result of this development approach, model code becomes coupled with and dependent on a specific modeling framework. Coupling to a specific framework makes migration to other frameworks and reuse of the code outside the original framework more difficult. This complicates collaboration between model developers wishing to share model code that ma y have been developed in a variety of languages and frameworks. This paper provides initial results of an exploratory investigation on the invasiveness of environmental modeling frameworks. Invasiveness is defined as th e coupling between application (i.e., model) and framework code used to implement the model. By comparing the implementation of an environmental model across several modeling frameworks, we aim to better understand the consequences of framework design. How frameworks present functionality to modelers through APIs can lead to consequences with respect to model development, model maintenance, reuse of model code, and ultimately collaboration among model developers. By measuring framework invasiveness, we hope to provide environmental modeling framework developers and environmental modelers with valuable in formation to assist in future development efforts. Eight implementations (six framework-based) of Thornthwaite, a simple water balance model, were made in a variety of environmental modeling frameworks and languages. A set of software metrics were proposed and applied to measure invasiveness between model implementation code and framework code. The metrics produced a rank ordering of invasiveness for the framework-based implementations of Thornthwaite. We compared model invasiveness results with several popular software metrics including size in lines of code (LOC), cyclomatic complexity, and object oriented coupling. To investigate software quality implications of framework invasiveness we checked for relationships between the Chidamber and Kemerer (1994) object oriented software metrics and our framework invasiveness measures. For the six framework-based implementations of Thornthwaite we found a five-fold variation in code size (LOC). We observed up to a seven-fold variation in total cyclomatic complexity, and a two to three-fold variation in object oriented coupling. For the model implementations we found that total size, total complexity, and total coupling all had a significant positive correlation. The raw count version of our invasiveness measures correlated with application size (LOC), total cyclomatic complexity, total efferent coupling (fan out) and total afferent coupling (fan in). Large size, complexity, and high levels of coupling between units (classes, modules) in a software system are often cited in software engineering as causes of high maintenance costs due to poor understandability and flexibility of the code. This study provides initial results but further investigation is desired to evaluate the utility of our invasiveness measurement approach as well as the software quality implications of framework invasiveness.
Improving Quantum Secret-Sharing Schemes
(Physical Review A, 9/17/2001) Nascimento, Anderson C.; Mueller-Quade, Joern; Imai, Hideki
We propose a protocol that enables a dealer to share a quantum secret with n players using less than n quantum shares for several access structures. For threshold schemes we derived an expression that shows how many quantum shares can be saved in this scheme. Also, several features that are available for classical secret-sharing schemes (and previously not known to be possible for quantum secret-sharing) become available with this protocol.
Cyberinfrastructure for Scalable Access to Stream Flow Analysis
(iEMSs 2014 International Congress on Environmental Modeling and Software - Bold Visions for Environmental Modelling, Seventh Biennial Meeting, 6/1/2014) Wible, Tyler; Lloyd, Wesley James; David, Olaf; Arabi, Mazdak
Traditionally the various components of flow analysis including flooding, drought, base - flow, pollutant loading, and duration curves have been examined independently by various analysis methods or software packages. A better approach would be to combine these multiple packages into a single web - tool to improve access . Infrastructure - as - a - Service (IaaS) cloud provides a scalable infrastructure for model implementation , which is a necessity of web services due to the characteristics of web traffic. IaaS centralizes the computational burden and overhead of multiple model runs from local computers to online servers. This paper demonstrates the scalability benefits of the Comprehensive Flow Analysis (CFA) tool in an IaaS environment . The CFA tool is available through the Environmental Risk Assessment Management System (eRAMS) website. eRAMS facilitates GIS data manipulation, visualization, and preparation of input information for models lik CFA . eRAMS uses the Cloud Services Innovation Platform (CSIP) to request runs of the analyses with in CFA. CSIP is an IaaS cloud modeling framework designed for executing various environmental models. This paper summarizes a scalability analysis of the analysis methods within CFA using CSIP in a cloud server environment.
Effectiveness of Elicitation Techniques in Distributed Requirements Engineering
(Requirements Engineering, 2002. Proceedings. IEEE Joint International Conference On, 1/1/2002) Lloyd, Wesley James; Rosson, Mary Beth; Arthur, James D.
Software development teams are often geographically distributed from their customers and end users. This creates significant communication and coordination challenges that impact the effectiveness of requirements engineering. Travel costs, and the local availability of quality technical staff increase the demand for effective distributed software development teams. This research reports an empirical study of how groupware can be used to aid distributed requirements engineering for a software development project. Six groups of seven to nine members were formed and divided into separate remote groups of customers and engineers. The engineers conducted a requirements analysis and produced a software requirements specification (SRS) document through distributed interaction with the remote customers. We present results and conclusions from the research including: an analysis of factors that effected the quality of the Software Requirements Specification document written at the conclusion of the requirements process and the effectiveness of requirements elicitation techniques which were used in a distributed setting for requirements gathering.
Mapping and Managing Organization Objectives: A Case Study of the Alto Maipo Hydroelectric Project in Chile
(Journal of Water Resources Planning and Management, 11/1/2021) Walters, Jeffrey P.; Alcayaga, Hernán; Busco, Carolina; Araya, Tamara
This study presents a process that uses the method of alliances, conflicts, tactics, objectives, and recommendations (MACTOR) to inform integrated water resources management (IWRM) strategies for complex, multiorganization hydroelectric projects. This process is applied to the Alto Maipo Hydroelectric Project (AMHP) in Chile. The process enabled qualitative and quantitative insight on the interconnected aspects of alignment and conflict between AMHP organizations by mapping the battlefield on which they converge or diverge based on their organizational objectives and relative levels of influence. Study findings reveal environmental protection and water provision as the core objectives around which conflicts center. Study findings also point to a nuanced power struggle between state and local organizations that undermines project productivity. Project recommendations focus on improving communication and collaboration between aligned yet siloed organizations and on improving the mechanisms for information flow and advocacy for the local community and governmental organizations. These findings demonstrate the utility of the MACTOR approach-as it is applied within the proposed process-as a way to inform IWRM strategies for multiorganization hydroelectric projects from a systems perspective
An ethnography of reason: following a recipe
(2025-06-20) Tenenberg, Josh
In this document, I carry out what Livingston (2008) calls an ethnography of reason as a way to make audible and visible the actions that I take in carrying out a simple task, that of cooking when following a written recipe. The ethnography of reason is a form of empirical description adapted from Livingston’s studies using ethnomethodological methods of inquiry. The ethnography of reason involves a first-person account of an individual carrying out a task within an environing context. The account produced makes explicit what the skilled actor does, often without conscious thought, while they are busy within the midst of the activity itself.

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