DOCSLIB.ORG

ETSI TR 102 659-2 V1.2.1 (2009-10) Technical Report

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text

Load more

ETSI TR 102 659-2 V1.2.1 (2009-10) Technical Report GRID; Study of ICT Grid interoperability gaps; Part 2: Interoperability Gaps and proposed solutions 2 ETSI TR 102 659-2 V1.2.1 (2009-10) Reference RTR/GRID-0001-2[2] Keywords analysis, directory, ICT, interoperability, testing ETSI 650 Route des Lucioles F-06921 Sophia Antipolis Cedex - FRANCE Tel.: +33 4 92 94 42 00 Fax: +33 4 93 65 47 16 Siret N° 348 623 562 00017 - NAF 742 C Association à but non lucratif enregistrée à la Sous-Préfecture de Grasse (06) N° 7803/88 Important notice Individual copies of the present document can be downloaded from: http://www.etsi.org The present document may be made available in more than one electronic version or in print. In any case of existing or perceived difference in contents between such versions, the reference version is the Portable Document Format (PDF). In case of dispute, the reference shall be the printing on ETSI printers of the PDF version kept on a specific network drive within ETSI Secretariat. Users of the present document should be aware that the document may be subject to revision or change of status. Information on the current status of this and other ETSI documents is available at http://portal.etsi.org/tb/status/status.asp If you find errors in the present document, please send your comment to one of the following services: http://portal.etsi.org/chaircor/ETSI_support.asp Copyright Notification No part may be reproduced except as authorized by written permission. The copyright and the foregoing restriction extend to reproduction in all media. © European Telecommunications Standards Institute 2009. All rights reserved. DECTTM, PLUGTESTSTM, UMTSTM, TIPHONTM, the TIPHON logo and the ETSI logo are Trade Marks of ETSI registered for the benefit of its Members. 3GPPTM is a Trade Mark of ETSI registered for the benefit of its Members and of the 3GPP Organizational Partners. LTE™ is a Trade Mark of ETSI currently being registered for the benefit of its Members and of the 3GPP Organizational Partners. GSM® and the GSM logo are Trade Marks registered and owned by the GSM Association. ETSI 3 ETSI TR 102 659-2 V1.2.1 (2009-10) Contents Intellectual Property Rights ................................................................................................................................ 7 Foreword ............................................................................................................................................................. 7 1 Scope ........................................................................................................................................................ 8 2 References ................................................................................................................................................ 8 2.1 Normative references ......................................................................................................................................... 9 2.2 Informative references ........................................................................................................................................ 9 3 Definitions and abbreviations ................................................................................................................. 15 3.1 Definitions ........................................................................................................................................................ 15 3.2 Abbreviations ................................................................................................................................................... 16 4 Methodology for Gap Analysis .............................................................................................................. 18 5 Specification Areas selected for Analysis .............................................................................................. 18 5.1 Service Level Agreements ................................................................................................................................ 18 5.1.1 Introduction................................................................................................................................................. 18 5.1.2 SLA Terminology ....................................................................................................................................... 18 5.1.3 Secondary Definitions................................................................................................................................. 21 5.1.4 Discussion ................................................................................................................................................... 21 5.1.5 Different types of SLA ............................................................................................................................... 22 5.2 Security ............................................................................................................................................................ 22 5.2.1 Introduction................................................................................................................................................. 22 5.2.2 Definitions .................................................................................................................................................. 22 5.2.3 Authentication ............................................................................................................................................. 23 5.3 Charging ........................................................................................................................................................... 25 5.3.1 Introduction................................................................................................................................................. 25 5.3.2 Charging Terminology ................................................................................................................................ 25 5.3.3 Offline Charging ......................................................................................................................................... 25 5.3.4 Online Charging Service ............................................................................................................................. 26 5.4 Service Discovery............................................................................................................................................. 26 5.4.1 Introduction................................................................................................................................................. 26 5.4.2 Terminology ............................................................................................................................................... 26 6 Case Studies ........................................................................................................................................... 27 7 Issues, Gaps and Overlaps ...................................................................................................................... 27 7.1 General issues gaps and overlaps ..................................................................................................................... 27 7.1.1 Architectural issues gaps and overlaps ....................................................................................................... 27 7.1.2 General Management issues gaps and overlaps .......................................................................................... 28 7.1.3 Grid Integration and implementation .......................................................................................................... 28 7.1.4 Grid and Cloud Computing ......................................................................................................................... 29 7.2 Service capability and operational issues ......................................................................................................... 29 7.2.1 Issues relating to SLA and QoS .................................................................................................................. 29 7.2.2 Issues relating to security ............................................................................................................................ 30 7.2.3 Issues relating to Charging ......................................................................................................................... 31 7.2.4 Issues relating to Service Discovery ........................................................................................................... 31 7.3 Gaps and overlaps arising from the EU FP6 Grids Survey .............................................................................. 32 8 Proposed Solutions ................................................................................................................................. 32 8.1 General Solutions ............................................................................................................................................. 32 8.1.1 Architectural Solutions ............................................................................................................................... 32 8.1.2 General management Solutions .................................................................................................................. 32 8.1.3 Grid Integration and implementation .........................................................................................................
Recommended publications
  • Adapting a Collaborative, Force-Feedback, Graphical User Interface to Best-Effort Networks

    Adapting a Collaborative, Force-Feedback, Graphical User Interface to Best-Effort Networks

    Adapting a Collaborative, Force-Feedback, Graphical User Interface to Best-E®ort Networks by Thomas C. Hudson A dissertation submitted to the faculty of the University of North Carolina at Chapel Hill in partial ful¯llment of the requirements for the degree of Doctor of Philosophy in the Department of Computer Science. Chapel Hill 2004 Approved by Advisor: Russell M. Taylor II Advisor: Kevin Je®ay Reader: Mary C. Whitton Gary Bishop F. Donelson Smith Richard Super¯ne ii iii Copyright °c 2004 Thomas C. Hudson ALL RIGHTS RESERVED iv v ABSTRACT THOMAS C. HUDSON: Adapting a Collaborative, Force-Feedback, Graphical User Interface to Best-E®ort Networks. (Under the direction of Russell M. Taylor II and Kevin Je®ay.) Latency is an unavoidable fact of distributed systems, and an unrelenting foe of in- terface usability. I present methods for lessening the impact of latency on distributed haptic, graphic, and collaborative interfaces. These three interfaces are present in the distributed nanoManipulator, a shared tool for remote operation of Atomic Force Microscopes. The work is carried out in the context of the Internet, where best-e®ort service means that network performance is not guaranteed and that applications must function under a wide range of conditions. The ability of a distributed control algorithm to tolerate latency is innately tied up with how data or operations in the algorithm are represented for transmission over the network. I introduce two new representations for haptics, the warped plane ap- proximation and local environment sampling, with superior latency tolerance. I show how image-based rendering is a useful representation for transferring the output of a remote graphics engine across the network, yielding a tenfold reduction in mean response time over video-based approaches, and how optimistic concurrency control is a useful representation for transmitting the actions of a remote collaborator across the network, requiring 85% less concurrency control overhead than pessimistic ap- proaches.
  • Computer Supported Cooperative Work

    Computer Supported Cooperative Work

    Computer Supported Co-operative Work Edited by Michel Beaudouin-Lafon Université Paris-Sud, France JOHN WILEY AND SONS Chichester • New York • Weinheim • Brisbane • Singapore • Toronto Copyright © 1999 by John Wiley & Sons Ltd, Baffins Lane, Chihester West Sussex PO19 1UD, England National 01234 779777 International(+44) 1234 779777 e-mail (for orders and customer service enquiries): [email protected] Visit our Home Page on http://www.wiley.co.uk or http://www.wiley.com All rights reserved. No part of this publication may be reproduced, stored in a retrieval system, or transmitted, in any form or by any means, electronic, mechanical, photocopying, recording, scanning or otherwise, except under the terms of the Copyright, Designs and Patents Act 1988 or under the terms of a licence issued by the Copyright Licensing Agency, 90 Tottenham Court Road, London, W1P 9HE, UK, without the permission in writing of the publisher. Other Wiley editorial offices John Wiley & Sons, Inc., 605 Third Avenue, New York, NY 10158-0012, USA WILEY-VCH Gmbh, Pappelallee 3, D-69469 Weinheim, Germany Jacaranda Wiley Ltd, 33 Park Road, Milton, Queensland 4064, Australia John Wiley & Sons (Asia) Pte Ltd, 2 Clementi Loop #02-01, Jin Xing Distripark, Singapore 129809 John Wiley & Sons (Canada) Ltd, 22 Worcester Road, Rexdale, Ontario M9W 1L1, Canada Library of Congress Cataloging-in-Publication Data Beaudouin-Lafon, Michel. Computer supported co-operative work / Michel Beaudouin-Lafon p. c. — (Trends in software ; 7) Includes bibliographical references and index. ISBN 0-471-96736-X (alk. paper) 1. Teams in the workplace — Computer networks. I. Title II. Series.
  • Computational Grids in Action: the National Fusion Collaboratory

    Computational Grids in Action: the National Fusion Collaboratory

    Computational Grids in Action: The National Fusion Collaboratory K. Keahey1 T. Fredian2 Q. Peng3 D. P. Schissel3 M. Thompson4 I. Foster1, 5 M. Greenwald2 D. McCune6 1 Mathematics and Computer Science Division, Argonne National Laboratory, Argonne, IL 60439 2Plasma Science and Fusion Center, MIT, Cambridge, MA 02139 3General Atomics, P.O. Box 85608, San Diego, California, 92186-5608 4Lawrence Berkeley National Laboratory, Berkeley, CA 94720 5 Department of Computer Science, University of Chicago, Chicago, IL 60657 6Princeton Plasma Physics Laboratory, Princeton, NJ 08543-0451 1. Introduction The term computational Grids [1] refers to infrastructures aimed at allowing users to access and/or aggregate potentially large numbers of powerful and sophisticated resources. More formally, Grids are defined as infrastructure allowing flexible, secure, and coordinated resource sharing among dynamic collections of individuals, institutions and resources referred to as virtual organizations [2]. In such environments, we encounter unique authentication, authorization, resource access, and resource discovery challenges. Each new Grid application facilitates a deeper understanding of these challenges and takes the Grid technology to increasing levels of functionality, performance, and robustness. In this paper we describe a new Grid application: the recently funded U.S. National Fusion Collaboratory and its potential for driving the understanding and development of computational Grids. The National Fusion Collaboratory project [3] was created to advance scientific understanding and innovation in magnetic fusion research by enabling more efficient use of existing experimental facilities through more effective integration of experiment, theory, and modeling. Magnetic fusion experiments operate in a pulsed mode producing plasmas of up to 10 seconds duration every 10 to 20 minutes, with multiple pulses per experiment.
  • Community Software Development with the Astrophysics Simulation Collaboratory

    Community Software Development with the Astrophysics Simulation Collaboratory

    CONCURRENCY AND COMPUTATION: PRACTICE AND EXPERIENCE Concurrency Computat.: Pract. Exper. 2002; 14:1289–1301 (DOI: 10.1002/cpe.688) Community software development with the Astrophysics Simulation Collaboratory Gregor von Laszewski1,∗,†, Michael Russell2, Ian Foster1,2, John Shalf3,4, Gabrielle Allen5, Greg Daues4,JasonNovotny3 and Edward Seidel4,5 1Mathematics and Computer Science Division, Argonne National Laboratory, Argonne, IL 60439, U.S.A. 2University of Chicago, Chicago, IL, U.S.A. 3Lawrence Berkeley National Laboratory, Berkeley, CA, U.S.A. 4National Center for Supercomputing Applications, Champaign, IL, U.S.A. 5Max-Planck-Institut f¨ur Gravitationsphysik, Albert-Einstein-Institut, Golm, Germany 6Washington University, St Louis, MI, U.S.A. SUMMARY We describe a Grid-based collaboratory that supports the collaborative development and use of advanced simulation codes. Our implementation of this collaboratory uses a mix of Web technologies (for thin- client access) and Grid services (for secure remote access to, and management of, distributed resources). Our collaboratory enables researchers in geographically disperse locations to share and access compute, storage, and code resources, without regard to institutional boundaries. Specialized services support community code development, via specialized Grid services, such as online code repositories. We use this framework to construct the Astrophysics Simulation Collaboratory, a domain-specific collaboratory for the astrophysics simulation community. This Grid-based collaboratory enables researchers in the field of numerical relativity to study astrophysical phenomena by using the Cactus computational toolkit. Copyright 2002 John Wiley & Sons, Ltd. KEY WORDS: collaboratory; Grid computing; Globus; Cactus; Java CoG Kit; Astrophysics Simulation Collaboratory ∗ Correspondence to: Gregor von Laszewski, Mathematics and Computer Science Division, Argonne National Laboratory, Argonne, IL 60439, U.S.A.
  • The Emergence of a Planetary-Scale Collaboratory For

    The Emergence of a Planetary-Scale Collaboratory For

    Larry Smarr e Emergence of a Planetary-Scale Collaboratory for Data-Intensive Research Introduction I had the good fortune to work with Alan Kay as part of the CSC Van- guard team in the 1990s and always valued the insightful critiques he would make of presentations during the Vanguard sessions. Although I knew about Alan’s fundamental contributions to user interface design, I came to under- stand also that he had a longtime interest in developing collaborative multi- user so ware to support many application areas of interest. is research with his colleagues eventually evolved into the Croquet so ware develop- ment kit (SDK), which can be used to support “highly scalable collaborative data visualization, virtual learning and problem solving environments, three- dimensional wikis, online gaming environments (MMORPGs), and privately maintained/interconnected multiuser virtual environments.”1 During the two decades that Alan and his colleagues were working on what became Croquet, the two institutes I founded, the National Center for Supercomputing Applications (NCSA) and the California Institute for Telecommunications and Information Technology (Calit2), were also deeply engaged in developing a series of collaboration environments, with a focus 1 http://en.wikipedia.org/wiki/Croquet_Project 77 Larry Smarr on collaborative analysis of data. Alan’s emphasis on simplicity and natural human-computer interfaces made a deep impression on me. I have kept these ideas in mind as the global team I was part of developed a working version of a collaboration metacomputer [16] as big as planet Earth, but with many of same characteristics as a personal computer. I briey describe the two tracks we followed: the rst was similar to Alan’s notion of a collaborative environment for sharing personal computer desk- tops and the second a series of experiments on tele-immersion, innovative so - ware/hardware environments that enable sharing of entire rooms for data intensive analysis using advanced technologies.
  • A Study of Spoken Audio Processing Using Machine Learning For

    A Study of Spoken Audio Processing Using Machine Learning For

    A Study of Spoken Audio Processing using Machine Learning for Libraries, Archives and Museums (LAM) 1Weijia Xu, 1Maria Esteva, 2Peter Cui, 2Eugene Castillo, 2Kewen Wang, 3Hanna-Robbins Hopkins, 3Tanya Clement, 4Aaron Choate, 1Ruizhu Huang 1 Texas Advanced Computing Center, 2 Department of Computer Science, 3 Department of English, 4 University of Texas Libraries University of Texas at Austin Austin, Texas USA Abstract— As the need to provide access to spoken word Machine Learning (ML) applications to assist LAM audio collections in libraries, archives, and museums (LAM) collections management has resulted in both admirers and increases, so does the need to process them efficiently and skeptics. As Ordelman et. al. [2] and others argue [3-6], consistently. Traditionally, audio processing involves listening to deploying automation in annotation and collections processing the audio files, conducting manual transcription, and applying could support LAM professionals charged with preserving and controlled subject terms to describe them. This workflow takes significant time with each recording. In this study, we investigate providing access to these materials. For example, ML tools can if and how machine learning (ML) can facilitate processing of be used to generate metadata with which users can easily search audio collections in a manner that corresponds with LAM best for items within a collection and that LAM professionals might practices. We use the StoryCorps collection of oral histories "Las otherwise have to assign manually [4,5]. While these solutions Historias," and fixed subjects (metadata) that are manually might improve and accelerate processing, there is a steep road assigned to describe each of them. Our methodology has two ahead towards researching, developing, and maintaining such main phases.
  • Human-Computer Interaction and Information Management Research

    Human-Computer Interaction and Information Management Research

    This page intentionally left blank. TABLE OF CONTENTS REPORT OVERVIEW .................................................................................................................1 1. INTRODUCTION AND PRIMER...................................................................................3 1.1 Why Do Humans Use Computing Systems? ..............................................................4 1.2 What Do Humans Use Computing Systems For?.......................................................6 1.3 How Do Humans and Computing Systems Use Data and Information?....................7 1.3.1 How Do Humans Use Data and Information? ...........................................11 1.3.2 How Do Computing Systems Use Data and Information? ........................11 1.3.3 How Can Humans and Computing Systems Best Work Together? ..........12 2. HCI&IM RESEARCH NEEDS......................................................................................15 2.1 Information Creation, Organization, Access, and Use .............................................15 2.2 Managing Information as an Asset ...........................................................................16 2.3 Human-Computer Interaction and Interaction Devices ............................................17 2.4 Evaluation Methods and Metrics ..............................................................................18 3. HCI&IM CG GOVERNMENT WORKSHOP - OCTOBER 22, 2001 ......................21 3.1 DARPA ....................................................................................................................21