World-wide Grid Research Articles

The Electrification of the World

It is unlikely there is a more momentous event in the creation of modern civilization than the invention of the electric light and its handmaiden, the worldwide grid. The 21st century Green Economy rests firmly on the foundation of the electric grid. Few know that the dynamo, the electric light – both arc and incandescent – and the electric grid were invented and launched in the late 1870s and early 1880s. This essay describes how and why these inventions happened. It is divided into two parts, each with its separate references, for the sake of clarity, as a great many important discoveries and technicalities had to be worked out each step of the way. Part One covers the development of the arc lamp and its “engine,” the dynamo. Part Two covers the invention of the long-burning carbon-based filament of the incandescent light bulb, as well as more powerful dynamos to supply power to thousands and soon millions of these new bulbs, and Edison’s visionary and pioneering construction of the revolutionary first electric grid. These developments seeded the construction of the universal worldwide grid in the 1890s and early 20th century. Their origins and history are integral to understanding the basis of our 21st century material civilization.

A framework for selecting the location of very large photovoltaic solar power plants on a global/supergrid

One of the important optimization applications (minimization and maximization) is the power grid systems. National electricity grids should be interconnected to develop larger regional grids (supergrids), and further integrated to build up a worldwide grid (global grid) for minimizing consumption of natural resources and maximizing economical useful life, recycling rate, and effective usage of natural resources. These supergrids and global grid concepts can only be developed through detailed and organized supportive research studies. This research study aims to find, define, identify, describe and select location selection factors of very large photovoltaic solar power plant investments on a global grid and supergrid concepts. Grey systems theory, fuzzy (Type-1 and 2) theories, Mamdani’s type fuzzy rule-based system, Interpretive Structural Modelling (ISM), Impact Matrix Cross-Reference Multiplication Applied to a Classification (MICMAC) tool, and Political, Economic, Social and Technological (PEST) framework and its extensions (SLEPT, PESTEL, PESTLE, STEEPLE, STEEPLED, DESTEP, STEER) are concurrently used in this study. Eleven (11) criteria are presented for preliminary screening (i.e. C1: global horizontal irradiation (GHI), C2: governments supergrid integration policy, C3: supergrid business climate and conditions, C4: High Voltage Direct Current (HVDC) and High Voltage Alternating Current (HVAC) electrification grid infrastructure, C5: land use, allocation and availability, C6: geological conditions, C7: political, war, terror & security, C8: topographical conditions, C9: climatic conditions, C10: water availability conditions, C11: natural disaster/hazard conditions), and 191 factors are presented for pre-feasibility investment stages. Findings can directly be used or taken as a basis for further analysis by researchers and practitioners.

Fast Height Conversion Method for BDS Receivers

In order to apply the positioning results of BDS receiver into engineering practice, geodetic height obtained from positioning calculation of receiver should be converted into normal height, therefore it is needed to calculate height anomaly. Also in order to meet the meter level height conversion demand, reduce the memory space consumption by height conversion program and accelerate the program running speed, this paper shows one fast height conversion computation method with the reduced order spherical harmonic coefficients of the gravity model, namely that the height anomaly computed respectively with spherical harmonic coefficients of EGM96 gravity model extending to degree 360 and order 360 and EGM08 earth gravity field extending to degree 2190 and order 2159 is deemed as benchmark, and summarizes the time consumption and relative accuracy of the fast height conversion method. According to the test and comparative analysis of height anomaly computed between world-wide grid points and Asia-Pacific region grid points, test results indicate that this height anomaly computation method with reduced-order spherical harmonic coefficients of EGM96 gravity model can meet the height conversion accuracy and speed demand for positioning results of BDS receivers all over the world or in Asia-Pacific region.

Economic-based Distributed Resource Management and Scheduling for Grid Computing

Computational Grids, emerging as an infrastructure for next generation computing, enable the sharing, selection, and aggregation of geographically distributed resources for solving large-scale problems in science, engineering, and commerce. As the resources in the Grid are heterogeneous and geographically distributed with varying availability and a variety of usage and cost policies for diverse users at different times and, priorities as well as goals that vary with time. The management of resources and application scheduling in such a large and distributed environment is a complex task. This thesis proposes a distributed computational economy as an effective metaphor for the management of resources and application scheduling. It proposes an architectural framework that supports resource trading and quality of services based scheduling. It enables the regulation of supply and demand for resources and provides an incentive for resource owners for participating in the Grid and motives the users to trade-off between the deadline, budget, and the required level of quality of service. The thesis demonstrates the capability of economic-based systems for peer-to-peer distributed computing by developing users' quality-of-service requirements driven scheduling strategies and algorithms. It demonstrates their effectiveness by performing scheduling experiments on the World-Wide Grid for solving parameter sweep applications.

Long Term Electricity Demand & Peak Power Load Forecasting Variables Identification & Selection

Electricity demand (kilowatt hour: kWh) and peak power load (kilowatt: kW) forecasting is very important for not only expansion planning purposes (long term), but also for dispatching purposes (short term). Hence, from the long term forecasting perspective to the very short term forecasting perspective, the nature of electricity demand and the peak power load forecasting has to be studied and understood very well. At first, the problem has to be understood very well, then the solution of this problem has to be studied and solved. These activities are in the scope of this research, development, demonstration, & deployment (RD 3 ) studies. The author thinks that the natural mechanisms of electricity demand and peak power load forecasting problem can be understood very well by finding, defining, identifying, and describing the factors (parameters, variables) that affect the electricity demand and peak power load. In this study, GATE is only used during corpus development as a backup check. R text mining package (Rtm) and TextSTAT are used as main text mining and analysis tools. 314 terms as candidate variable terms are found by this text analysis. Afterwards, all variables are studied and analyzed by a grey based natural reasoning with simple weighted average approach (WA) (only for long term factors as preliminary in this application) (on way of simple additive weighting method: SAW). Finally, 43 terms (e. g. population, weather, climate, economy, price) for variables are found for infant and mature RD 3 studies of 100% renewable energy (RE) worldwide grid (Global Grid). Findings of this study can also be used in other grid types. It is believed that a specific dictionary and encyclopedia in this particular subject should be developed for researchers common sense which will also help building of the Global Grid Prediction Systems (G 2 PS).

Long Term Electricity Demand & Peak Power Load Forecasting Variables Identification & Selection

Electricity demand (kilowatt hour: kWh) and peak power load (kilowatt: kW) forecasting is very important for not only expansion planning purposes (long term), but also for dispatching purposes (short term). Hence, from the long term forecasting perspective to the very short term forecasting perspective, the nature of electricity demand and the peak power load forecasting has to be studied and understood very well. At first, the problem has to be understood very well, then the solution of this problem has to be studied and solved. These activities are in the scope of this research, development, demonstration, & deployment (RD³) studies. The author thinks that the natural mechanisms of electricity demand and peak power load forecasting problem can be understood very well by finding, defining, identifying, and describing the factors (parameters, variables) that affect the electricity demand and peak power load. In this study, GATE is only used during corpus development as a backup check. R text mining package (Rtm) and TextSTAT are used as main text mining and analysis tools. 314 terms as candidate variable terms are found by this text analysis. Afterwards, all variables are studied and analyzed by a grey based natural reasoning with simple weighted average approach (WA) (only for long term factors as preliminary in this application) (on way of simple additive weighting method: SAW). Finally, 43 terms (e. g. population, weather, climate, economy, price) for variables are found for infant and mature RD³ studies of 100% renewable energy (RE) worldwide grid (Global Grid). Findings of this study can also be used in other grid types. It is believed that a specific dictionary and encyclopedia in this particular subject should be developed for researchers common sense which will also help building of the Global Grid Prediction Systems (G²PS).

The Evolution of Cloud Computing in ATLAS

The ATLAS experiment at the LHC has successfully incorporated cloud computing technology and cloud resources into its primarily grid-based model of distributed computing. Cloud R&D activities continue to mature and transition into stable production systems, while ongoing evolutionary changes are still needed to adapt and refine the approaches used, in response to changes in prevailing cloud technology. In addition, completely new developments are needed to handle emerging requirements. This paper describes the overall evolution of cloud computing in ATLAS. The current status of the virtual machine (VM) management systems used for harnessing Infrastructure as a Service resources are discussed. Monitoring and accounting systems tailored for clouds are needed to complete the integration of cloud resources within ATLAS' distributed computing framework. We are developing and deploying new solutions to address the challenge of operation in a geographically distributed multi-cloud scenario, including a system for managing VM images across multiple clouds, a system for dynamic location-based discovery of caching proxy servers, and the usage of a data federation to unify the worldwide grid of storage elements into a single namespace and access point. The usage of the experiment's high level trigger farm for Monte Carlo production, in a specialized cloud environment, is presented. Finally, we evaluate and compare the performance of commercial clouds using several benchmarks.

ALATO: An efficient intelligent algorithm for time optimization in an economic grid based on adaptive stochastic Petri net

Cost and execution time are important issues in economic grids, which are widely used for parallel computing. This paper proposes ALATO, an intelligent algorithm based on learning automata and adaptive stochastic Petri nets (ASPNs) that optimizes the execution time for tasks in economic grids. ASPNs are based on learning automata that predict their next state based on current information and the previous state and use feedback from the environment to update their state. The environmental reactions are extremely helpful for teaching Petri nets in dynamic environments. We use SPNP software to model ASPNs and evaluate execution time and costs for 200 tasks with different parameters based on World Wide Grid standard resources. ALATO performs better than all other heuristic methods in reducing execution time for these tasks.

После EGI — WGI?

This article concerns a short review of history and author’s estimation of realization state in projects for data handling, based on use of Grid-technologies (in particular, in frames of European Grid Initiative project: EGI). Some problems are mentioned, which concern the possible WGI (Worldwide Grid Initiative project) realization.

Historical distribution, habitat requirements and feeding ecology of the genus Equus (Perissodactyla)

Abstract Dietary traits of nine extant Equus species (E. africanus, E. ferus, E. grevyi, E. hartmannae, E. hemionus, E. khur, E. kiang, E. quagga and E. zebra) were reconstructed and ranked in a continuum reflecting the relative proportions of abrasion and attrition. In order to match them automatically with climatic data, localities were referenced within a 2° worldwide grid system using geographical information system software. The mesowear score was used as a proxy variable to test the covariance of diet with mean annual precipitation, evapotranspiration, mean annual climatic water balance and mean annual temperature. Seven of the nine equid species presented mesowear signatures indicating a grass‐dominated diet, and we found interspecific as well as intraspecific variability. Non‐gramineous food components shifted the equilibrium towards the attrition‐dominated end in E. africanus and E. khur, indicating an intermediate diet. Especially in E. zebra, additional sources of exogenous abrasives (grit and soil) might increase dietary abrasiveness. In E. quagga, dietary flexibility and the capability to cope with increased abrasiveness are considered keystone factors allowing its large geographical range. The broad, species‐specific range of climate parameters associated with the habitats was used to define the thresholds of the species' feeding niches. Our data suggest that climate as represented by the variables we used does not, in the first instance, relate to the tooth wear signature of equids. We thus conclude that the tooth wear signature is more specific to the feeding strategy and should be regarded a dietary trait rather than an immediate imprint of climate. However, tooth wear can be used to infer local dietary traits and might therefore become an important tool in conservation management.

Seeing Like the OECD on Tax

Scott's account of state-making is premised on the ‘legibility’ of society, facilitating administration by replacing idiosyncratic and particularistic local arrangements with a uniform bureaucratic grid. Along with conscription, extracting tax was the primary motivation behind this transformation. With the growth in cross-border economic relations, the current challenge for tax collectors is to make finance and banking legible at the global scale, moving from idiosyncratic and particularistic national arrangements towards a world-wide uniform bureaucratic grid. This is believed to be necessary to defeat would-be tax evaders looking to profit from the gaps and incompatibilities between different national tax systems. The Organisation for Economic Co-operation and Development (OECD) is the main agent in homogenising tax data and procedures, and facilitating the exchange of tax information between states. As such, ‘seeing like a state’ on tax gives way to ‘seeing like the OECD’.

GOCDB, a topology repository for a worldwide grid infrastructure

All grid projects have to deal with topology and operational information like resource distribution, contact lists and downtime declarations. Storing, maintaining and publishing this information properly is one of the key elements to successful grid operations. The solution adopted by EGEE and WLCG projects is a central repository that hosts this information and makes it available to users and client tools. This repository, known as GOCDB, is used through EGEE and WLCG as an authoritative primary source of information for operations, monitoring, accounting and reporting. After giving a short history of GOCDB, the paper describes the current architecture of the tool and gives an overview of its well established development workflows and release procedures. It also presents different collaboration use cases with other EGEE operations tools and deals with the High Availability mechanism put in place to address failover and replication issues. It describes ongoing work on providing web services interfaces and gives examples of integration with other grid projects, such as the NGS in the UK. The paper finally presents our vision of GOCDB's future and associated plans to base its architecture on a pseudo object database model, allowing for its distribution across the 11 EGEE regions. This will be one of the most challenging works to achieve during the third phase of EGEE in order to prepare for a sustainable European Grid Infrastructure.

A model assisted ionospheric electron density reconstruction method based on vertical TEC data ingestion

A technique to reconstruct the electron density of the ionosphere starting from total electron content values has been developed using the NeQuick ionospheric electron density model driven by its effective ionization parameter Az. The technique is based on the computation of Az values for a suitable worldwide grid of points. A simple way to obtain relevant Az grids is to use global vertical Total Electron Content (TEC) maps to define for each grid point as Az value, the one that minimizes the difference between the experimental and the modeled vertical TEC. Having a global grid of Az values it is possible to compute the electron density at any point in the ionosphere using NeQuick. As a consequence, slant TEC values for specific ground station to satellite links or ionosphere peak parameter values at any location can be calculated. The results of the comparisons between experimental and reconstructed slant TEC as well as experimental and reconstructed peak parameters values indicate that the proposed reconstruction method can be used to reproduce the observed ionosphere in a realistic way.

GMBS: A new middleware service for making grids interoperable

Grid resource management has been a highly studied research field since Grids were born. Though well-designed, evaluated and widely used resource brokers and meta-schedulers have been developed, new capabilities are still required, while the major demand is for interoperability support. Most of the existing brokering solutions can hardly cross the borders of current middleware systems that are lacking the support of these requirements. In this paper we (i) investigate the current resource management solutions from the lowest to the highest level of the Grid middleware, (ii) examine and compare their connections by presenting an anatomy that helps users to grasp the basics of their operation and the researchers to identify common components and open issues. Then we (iii) introduce meta-brokering, which enables higher level resource management by utilizing existing Grid brokers, and provide an implementation of this solution, the Grid Meta-Broker Service, which is a new interoperable grid middleware service for interconnecting Grid islands to compose a World Wide Grid, where users and portals can transparently utilize a growing number of Grids in the future. Finally we (iv) evaluate the presented solution in a simulated Grid environment using real workloads.

GridPP: the UK grid for particle physics

The start-up of the Large Hadron Collider (LHC) at CERN, Geneva, presents a huge challenge in processing and analysing the vast amounts of scientific data that will be produced. The architecture of the worldwide grid that will handle 15 PB of particle physics data annually from this machine is based on a hierarchical tiered structure. We describe the development of the UK component (GridPP) of this grid from a prototype system to a full exploitation grid for real data analysis. This includes the physical infrastructure, the deployment of middleware, operational experience and the initial exploitation by the major LHC experiments.

Resolution of large symmetric eigenproblems on a world-wide grid

We propose a parallel and distributed application for the resolution of the large real symmetric eigenproblem on world-wide heterogeneous grids. It is based on the explicit restarted Lanczos algorithm which is a Krylov subspace method. We take into account the specificities of computational resources and deal with communication constraints over the internet. We propose techniques such as out-of-core and data persistence. We also show that a restarted algorithm and the combination of several paradigms of parallelism are relevant in this context. The results of the experiments stress the impact of the main numerical parameters of the Lanczos method. We also compare many platform configurations built on the top of two complementary experimental environments. We first use a realistic world-wide grid harnessing two geographical sites, in France and in Japan, interconnected by the internet. Then, we use the French national testbed Grid5000. We conclude on the scalability of our application and we forecast the next bounding factor of the implementation. It can be solved by means of a dedicated data management layer such as Omni Storage.

Global grid user support—building a worldwide distributed user support infrastructure

The organization and management of the user support in a global e-science computing infrastructure such as EGEE is one of the challenges of the grid. Given the widely distributed nature of the organisation, and the spread of expertise for installing, configuring, managing and troubleshooting the grid middleware services, a standard centralized model could not be deployed in EGEE. This paper presents the model used in EGEE for building a reliable infrastructure for user, virtual organisation and operations support. The model for supporting a production quality infrastructure for scientific applications will be described in detail. The advantages of the chosen model will be presented and the possible difficulties will be discussed. We will describe the ongoing efforts to build a worldwide grid user support infrastructure in the framework of WLCG by achieving interoperability between the EGEE and OSG user support systems. In this paper we will also describe a scheme of how knowledge management can be used in grid user support and first steps towards a realisation in the framework of the EGEE user support infrastructure.

Geographical failover for the EGEE-WLCG grid collaboration tools

Worldwide grid projects such as EGEE and WLCG need services with high availability, not only for grid usage, but also for associated operations. In particular, tools used for daily activities or operational procedures are considered to be critical. The operations activity of EGEE relies on many tools developed by teams from different countries. For each tool, only one instance was originally deployed, thus representing single points of failure. In this context, the EGEE failover problem was solved by replicating tools at different sites, using specific DNS features to automatically failover to a given service. A new domain for grid operations (gridops.org) was registered and deployed following DNS testing in a virtual machine (vm) environment using nsupdate, NS/zone configuration and fast TTLs. In addition, replication of databases, web servers and web services have been tested and configured. In this paper, we describe the technical mechanism used in our approach to replication and failover. We also describe the procedure implemented for the EGEE/WLCG CIC Operations Portal use case. Furthermore, we present the interest in failover procedures in the context of other grid projects and grid services. Future plans for improvements of the procedures are also described.

Estimating the impacts of climate change and urbanization on building performance

Over the past 15 years, much scientific work has been published on the potential human impacts on climates. For their Third Assessment Report in 2001, the United Nations International Programme on Climate Change developed a set of economic development scenarios, which were then run with the four major general circulation models (GCM) to estimate the anthropogenesis-forced climate change. These GCMs produce worldwide grids of predicted monthly temperature, cloud, and precipitation deviations from the period 1961–1990. As this period is the same used for several major typical meteorological year data sets, these typical data sets can be used as a starting point for modifying weather files to represent predicted climate change. Over the past 50 years, studies of urban heat islands (UHI) or urbanization have provided detailed measurements of the diurnal and seasonal patterns and differences between urban and rural climatic conditions. While heat islands have been shown to be a function of both population and microclimatic and site conditions, they can be generalized into a predictable diurnal and seasonal pattern. Although the scientific literature is full of studies looking at the impact of climate change driven by human activity, there is very little research on the impact of climate change or urban heat islands on building operation and performance across the world. This article presents the methodology used to create weather files which represent climate change scenarios in 2100 and heat island impacts today. For this study, typical and extreme meteorological weather data were created for 25 locations (20 climate regions) to represent a range of predicted climate change and heat island scenarios for building simulation. Then prototypical small office buildings were created to represent typical, good, and low-energy practices around the world. The simulation results for these prototype buildings provide a snapshot view of the potential impacts of the set of climate scenarios on building performance. This includes location-specific building response, such as fuel swapping as heating and cooling ratios change, impacts on environmental emissions, impacts on equipment use and longevity comfort issues, and how low-energy building design incorporating renewables can significantly mitigate any potential climate variation. In this article, examples of how heat island and climate change scenarios affect diurnal patterns are presented as well as the annual energy performance impacts for three of the 25 locations. In cold climates, the net change to annual energy use due to climate change will be positive – reducing energy use on the order of 10% or more. For tropical climates, buildings will see an increase in overall energy use due to climate change, with some months increasing by more than 20% from current conditions. Temperate, mid-latitude climates will see the largest change but it will be a swapping from heating to cooling, including a significant reduction of 25% or more in heating energy and up to 15% increase in cooling energy. Buildings which are built to current standards such as ASHRAE/IESNA Standard 90.1-2004 will still see significant increases in energy demand over the twenty-first century. Low-energy buildings designed to minimize energy use will be the least affected, with impacts in the range of 5–10%. Unless the way buildings are designed, built, and operated changes significantly over the next decades, buildings will see substantial operating cost increases and possible disruptions in an already strained energy supply system.

Grid-Enabled High-Throughput In Silico Screening Against Influenza A Neuraminidase

Encouraged by the success of the first EGEE biomedical data challenge against malaria (WISDOM), the second data challenge battling avian flu was kicked off in April 2006 to identify new drugs for the potential variants of the influenza A virus. Mobilizing thousands of CPUs on the Grid, the six-week-long high-throughput screening activity has fulfilled over 100 CPU years of computing power and produced around 600 gigabytes of results on the Grid for further biological analysis and testing. In the paper, we demonstrate the impact of a worldwide Grid infrastructure to efficiently deploy large-scale virtual screening to speed up the drug design process. Lessons learned through the data challenge activity are also discussed.