Resources and Services of the EGEE Production Infrastructure

This paper presents the pan-European EGEE Grid focusing on aspects such as production infrastructure, the management tools and the operational services offered. Usage statistics and the provided Quality of Service are analysed to assess the maturity level, the current penetration of Grid technologies in Europe and the current expansion trends. Being EGEE a large distributed infrastructure, operations are a joint effort of different regional centres with central coordination. EGEE operations rely on a common and agreed set of procedures, policies and interfaces, which are the foundation of operational services such as middleware deployment, Grid oversight, accounting, operational security management and support. A transition is in place to lead EGEE to a more sustainable approach based on a set of integrated National Grid Initiatives. With the support of the EGI-InSPIRE project the EGEE e-infrastructure and its services will migrate into a new governance model for the future sustainability of Grids in Europe.     

Towards a Powerful European DCI Based on Desktop Grids

Service Grids like the EGEE Grid can not provide the required number of resources for many VOs. Therefore extending the capacity of these VOs with volunteer or institutional desktop Grids would significantly increase the number of accessible computing resources that can particularly advantageously be exploited in case of parameter sweep applications. This objective has been achieved by the EDGeS project that built a production infrastructure enabling the extension of gLite VOs with several volunteer and institutional desktop Grids. The paper describes the technical solution of integrating service Grids and desktop Grids and, the actual EDGeS production infrastructure. The main objectives and current achievements of the follow-up EDGI project have also been described showing how the existing EDGeS infrastructure can be further extended with clouds.     

ComBos: A complete simulator of Volunteer Computing and Desktop Grids

Volunteer Computing is a type of distributed computing in which ordinary people donate their idle computer time to science projects like SETI@Home, Climateprediction.net and many others. In a similar way, Desktop Grid Computing is a form of distributed computing in which an organization uses its existing computers to handle its own long-running computational tasks. BOINC is the main middleware that provides a software platform for Volunteer Computing and desktop grid computing, and it became generalized as a platform for distributed applications in areas as diverse as mathematics, medicine, molecular biology, climatology, environmental science, and astrophysics. In this paper we present a complete simulator of BOINC infrastructures, called ComBoS. Although there are other BOINC simulators, none of them allow us to simulate the complete infrastructure of BOINC. Our goal was to create a complete simulator that, unlike the existing ones, could simulate realistic scenarios taking into account the whole BOINC infrastructure, that other simulators do not consider: projects, servers, network, redundant computing, scheduling, and volunteer nodes. The outputs of the simulations allow us to analyze a wide range of statistical results, such as the throughput of each project, the number of jobs executed by the clients, the total credit granted and the average occupation of the BOINC servers. The paper describes the design of ComBoS and the results of the validation performed. This validation compares the results obtained in ComBoS with the real ones of three different BOINC projects (Einstein@Home, SETI@Home and LHC@Home). Besides, we analyze the performance of the simulator in terms of memory usage and execution time. The paper also shows that our simulator can guide the design of BOINC projects, describing some case studies using ComBoS that could help designers verify the feasibility of BOINC projects.     

Scheduling for Responsive Grids

Grids are facing the challenge of seamless integration of the Grid power into everyday use. One critical component for this integration is responsiveness, the capacity to support on-demand computing and interactivity. Grid sched uling is involved at two levels in order to provide responsiveness: the policy level and the implementation level. The main contributions of this paper are as follows. First, we present a detailed analysis of the performance of the EGEE Grid with respect to responsiveness. Second, we examine two user-level schedulers located between the general scheduling layer and the application layer. These are the DIANE (distributed analysis environment) framework, a general-purpose overlay system, and a specialized, embedded scheduler for gPTM3D, an interactive medical image analysis application. Finally, we define and demonstrate a virtualization scheme, which achieves guaranteed turnaround time, schedulability analysis, and provides the basis for differentiated services. Both methods target a brokering-based system organized as a federation of batch-scheduled clusters, and an EGEE implementation is described.     

What Does Grid Computing Cost?

Grid computing has gained considerable attention in research and industry. High expectations are associated with the approach. However, so far only few papers have been published about the costs caused by Grid computing. In this article we pursue two main goals: to analyze the different types of costs and to determine the total costs of a resource provider. Our approach is based on the discussion of general cost categories that have to be taken into account. We give concrete numbers for the different categories and use these numbers to estimate the costs in two real life Grids: the EGEE project and the Grid of the pharmaceutical company Novartis. A summarizing discussion concludes the paper.     

Dynamic scheduling for heterogeneous Desktop Grids

Desktop Grids have emerged as an important methodology to harness the idle cycles of millions of participant desktop PCs over the Internet. However, to effectively utilize the resources of a Desktop Grid, it is necessary to use scheduling policies suitable for such systems. In this paper, we analyze the performance of a policy which is shown to perform well in highly heterogeneous Desktop Grids. The policy utilizes the solution to a linear programming (LP) problem which maximizes system capacity. We suggest robust modifications to address several limitations of the policy.     

Multi-objective Reinforcement Learning for Responsive Grids

Grids organize resource sharing, a fundamental requirement of large scientific collaborations. Seamless integration of Grids into everyday use requires responsiveness, which can be provided by elastic Clouds, in the Infrastructure as a Service (IaaS) paradigm. This paper proposes a model-free resource provisioning strategy supporting both requirements. Provisioning is modeled as a continuous action-state space, multi-objective reinforcement learning (RL) problem, under realistic hypotheses; simple utility functions capture the high level goals of users, administrators, and shareholders. The model-free approach falls under the general program of autonomic computing, where the incremental learning of the value function associated with the RL model provides the so-called feedback loop. The RL model includes an approximation of the value function through an Echo State Network. Experimental validation on a real data-set from the EGEE Grid shows that introducing a moderate level of elasticity is critical to ensure a high level of user satisfaction.     

Grid Interoperability Based on a Formal Design

We can distinguish two different Grid concepts: desktop and service Grids. Both Grid concepts have their advantages and disadvantages, however these are different. For example desktop Grids are a cost-effective platform, but sometimes unreliable. On the other hand service Grids are highly reliable, but need remarkable funding. The aim of Grid interoperability is to combine the advantages of the different Grid concepts, so the integrated infrastructure offers the best of both concepts. Within the paper we define the Grid interoperability problem, and approximate to the generic architecture through a formal model. We prove formally that the resulting architecture solves the Grid interoperability problem, and is generic enough to interconnect different Grid infrastructures with minor work. We also show in the paper that the formal concept can be applied for creating a gLite to BOINC bridge, and the performance of the core bridge implementation is satisfactory.     

The ShareGrid Peer-to-Peer Desktop Grid: Infrastructure,Applications, and Performance Evaluation

Peer-to-Peer (P2P) Desktop Grids are computing infrastructures that aggregate a set of desktop-class machines in which all the participating entities have the same roles, responsibilities, and rights. In this paper, we present ShareGrid, a P2P Desktop Grid infrastructure based on the OurGrid middleware, that federates the resources provided by a set of small research laboratories to easily share and use their computing resources. We discuss the techniques and tools we employed to ensure scalability, efficiency, and usability, and describe the various applications used on it. We also demonstrate the ability of ShareGrid of providing good performance and scalability by reporting the results of experimental evaluations carried out by running various applications with different resource requirements. Our experience with ShareGrid indicates that P2P Desktop Grids can represent an effective answer to the computing needs of small research laboratories, as long as they provide both ease of management and use, and good scalability and performance.     

Achieving efficiency, quality of service and robustness in multi-organizational Grids

Scalability, flexibility, quality of service provisioning, efficiency and robustness are the desired characteristics of most computing systems. Although the emerging Grid computing paradigm is scalable and flexible, achieving both efficiency and quality of service provisioning in Grids is a challenging task but is necessary for the wide adoption of Grids. Grid middleware should also be robust to uncertainties such as those in user-estimated runtimes of Grid applications. In this paper, we present a complete middleware framework for Grids that achieves user satisfaction by providing QoS guarantees for Grid applications, cost effectiveness by efficiently utilizing resources and robustness by intelligently handling uncertain runtimes of applications.     

Customizable execution environments for evolutionary computation using BOINC + virtualization

Evolutionary algorithms (EAs) consume large amounts of computational resources, particularly when they are used to solve real-world problems that require complex fitness evaluations. Beside the lack of resources, scientists face another problem: the absence of the required expertise to adapt applications for parallel and distributed computing models. Moreover, the computing power of PCs is frequently underused at institutions, as desktops are usually devoted to administrative tasks. Therefore, the proposal in this work consists of providing a framework that allows researchers to massively deploy EA experiments by exploiting the computing power of their instituions’ PCs by setting up a Desktop Grid System based on the BOINC middleware. This paper presents a new model for running unmodified applications within BOINC with a web-based centralized management system for available resources. Thanks to this proposal, researchers can run scientific applications without modifying the application’s source code, and at the same time manage thousands of computers from a single web page. Summarizing, this model allows the creation of on-demand customized execution environments within BOINC that can be used to harness unused computational resources for complex computational experiments, such as EAs. To show the performance of this model, a real-world application of Genetic Programming was used and tested through a centrally-managed desktop grid infrastructure. Results show the feasibility of the approach that has allowed researchers to generate new solutions by means of an easy to use and manage distributed system.     

Grid-enabled Virtual Screening Against Malaria

WISDOM is an international initiative to enable a virtual screening pipeline on a Grid infrastructure. Its first attempt was to deploy large scale in silico docking on a public Grid infrastructure. Protein–ligand docking is about computing the binding energy of a protein target to a library of potential drugs using a scoring algorithm. Previous deployments were either limited to one cluster, to Grids of clusters in the tightly protected environment of a pharmaceutical laboratory or to desktop Grids. The first large scale docking experiment ran on the EGEE Grid production service from 11 July 2005 to 19 August 2005 against targets relevant to research on malaria and saw over 41 million compounds docked for the equivalent of 80 years of CPU time. Up to 1,700 computers were simultaneously used in 15 countries around the world. Issues related to the deployment and the monitoring of the in silico docking experiment as well as experience with Grid operation and services are reported in the paper. The main problem encountered for such a large scale deployment was the Grid infrastructure stability. Although the overall success rate was above 80%, a lot of monitoring and supervision was still required at the application level to resubmit the jobs that failed. But the experiment demonstrated how Grid infrastructures have a tremendous capacity to mobilize very large CPU resources for well targeted goals during a significant period of time. This success leads to a second computing challenge targeting avian flu neuraminidase N1.     

SZTAKI Desktop Grid (SZDG): A Flexible and Scalable Desktop Grid System

SZTAKI Desktop Grid (SZDG) is an extension of BOINC in order to make it more flexible, versatile and scalable in terms of enabling the interconnection of different BOINC projects and execution of parameter sweep applications from a generic, high level user interface without the intervention of the BOINC project administrator. The paper describes the main concepts and features of SZDG. Among the many novel features the two most important will be described in detail. First, the paper describes those extensions that enable the easy development and execution of parameter sweep applications on SZDGs. The second part of the paper describes how SZDGs can be organized into a hierarchical interconnection scheme that enables to use SZDGs as building blocks to create higher level SZDGs.     

Provide Virtual Distributed Environments for Grid computing on demand

Grid users always expect to meet some challenges to employ Grid resources, such as customized computing environment and QoS support. In this paper, we propose a new methodology for Grid computing – to use virtual machines as computing resources and provide Virtual Distributed Environments (VDE) for Grid users. It is declared that employing virtual environment for Grid computing can bring various advantages, for instance, computing environment customization, QoS guarantee and easy management. A light weight Grid middleware, Grid Virtualization Engine, is developed accordingly to provide functions of building virtual environment for Grids. We also present a typical use case, on-demand build a virtual e-Science infrastructure to justify the methodology.     

Coordinated harnessing of the IRISGrid and EGEE testbeds with GridWay

Since the late 1990s, we have witnessed an extraordinary development of Grid technologies. Nowadays, different Grids are being deployed within the context of a growing number of national and transnational research projects. However, the coexistence of those different infrastructures involves two challenging issues, namely: (i) simultaneous and coordinated use of resources from different Grids, from the end user perspective; and (ii) the simultaneous contribution of resources to different Grids, from the resource owner perspective. In this paper, we demonstrate that a decentralized and “end-to-end” scheduling and execution system can efficiently interoperate different Grids. In particular, we evaluate the coordinated use of the EGEE and IRISGrid testbeds in the execution of a Bioinformatics application. Results show the feasibility of building loosely coupled computational Grid environments only based on Globus services, while obtaining non-trivial levels of quality of service, in terms of performance and reliability. Such approach allows a straightforward resource sharing since the resources are accessed by using de facto standard protocols and interfaces.     

Using a Simple Prioritisation Mechanism to Effectively Interoperate Service and Opportunistic Grids in the EELA-2 e-Infrastructure

Grids currently in production can be broadly classified as either service Grids, composed of dedicated resources, or opportunistic Grids that harvest the computing power of non-dedicated resources when they are idle. While a service Grid provides high and well defined levels of quality of service, an opportunistic Grid provides only a best-effort service. Nevertheless, since opportunistic Grids do not require resources to be fully dedicated to the Grid, they have the potential to assemble a much larger number of resources. Moreover, these Grids cater very well to the execution of the so-called embarrassingly parallel applications, a type of application that is frequently found in practice, and that comprises the largest portion of the typical workload processed in production Grid systems. The EELA-2 e-infrastructure is comprised of a service Grid and an opportunistic Grid that federates computing resources from scientific institutions in both Europe and Latin America. Due to the complementary characteristics of these two types of Grids, a lot of attention has recently been placed in how to interoperate them. In this paper we focus on the less studied problem of assessing the feasibility of such interoperation. We analyse different prioritisation policies that define when the resources of one Grid can be used to run jobs originating from the other. Our results show that in the absence of a suitable prioritisation policy, the benefits that the users of one Grid may have, frequently come with an important negative impact on the users of the other Grid. We also show that a simple reciprocation mechanism is capable of arbitrating the interoperation in such a way that, whenever possible, users profit from the interoperation and, in no case, this benefit leads to a noticeable reduction on the quality of service that the users would experience were the Grids not to interoperate. We conclude discussing how we have implemented, in the context of the EELA-2 project, this prioritisation mechanism, allowing the effective interoperation of a service Grid based on the gLite middleware with an opportunistic Grid that uses the OurGrid middleware.     

The AMGA Metadata Service

We present the AMGA metadata catalogue, which was developed as part of the EGEE (enabling Grids for EsciencE) project’s gLite Grid middleware. AMGA provides access to meta data for files stored on the Grid, as well as a simplified general access to relational data stored in database systems. Design and implementation of AMGA was done in close collaboration with the very diverse EGEE user community to make sure all functionality, performance and security requirements were met. In particular, AMGA targets the needs of the high energy physics community to rapidly access very large amounts of metadata, as well as the needs for security of the biomedical community. AMGA therefore tightly integrates fine grained access control making use of a virtual organisation management system. In addition, it offers advanced federation and features to increase dependability, performance and data security.     

Definition and Implementation of a SAML-XACML Profile for Authorization Interoperability Across Grid Middleware in OSG and EGEE

In order to ensure interoperability between middleware and authorization infrastructures used in the Open Science Grid (OSG) and the Enabling Grids for E-science (EGEE) projects, an Authorization Interoperability activity was initiated in 2006. The interoperability goal was met in two phases: firstly, agreeing on a common authorization query interface and protocol with an associated profile that ensures standardized use of attributes and obligations; and secondly implementing, testing, and deploying on OSG and EGEE, middleware that supports the interoperability protocol and profile. The activity has involved people from OSG, EGEE, the Globus Toolkit project, and the Condor project. This paper presents a summary of the agreed-upon protocol, profile and the software components involved.     

Fault tolerant and prioritized scheduling in OGSA‐based mobile Grids

Grids and mobile Grids can form the basis and the enabling technology for pervasive and utility computing due to their ability to being open, highly heterogeneous and scalable. In this paper we present a scheme for advancing quality of service (QoS) attributes, such as fault tolerance and prioritized scheduling, in OGSA‐based mobile Grids. The fault tolerance is achieved by producing and managing sufficient replicas of tasks submitted for execution on the mobile Grid resources. We design a simple and efficient prioritization scheme, which allows the scheduling of the tasks submitted by the Grid users as distinguished priorities that can be managed and exploited as a QoS parameter by the Grid infrastructure operator. The results that are presented show the efficiency of the proposed scheme in being simple and additionally enriching with reliability and QoS features the applications that are built on the concept of mobile Grids. Copyright © 2008 John Wiley & Sons, Ltd.