Cloud, Grid and High Performance Computing: Emerging Applications Emmanuel Udoh Indiana Institute of Technology, USA Senior Editorial Director: Editorial Director: Director of Book Publications: Acquisitions Editor: Development Editor: Production Editor: Typesetters: Print Coordinator: Cover Design: Kristin Klinger Lindsay Johnston Julia Mosemann Erika Carter Hannah Abelbeck Sean Woznicki Michael Brehm, Keith Glazewski, Milan Vracarich, Jr Jamie Snavely Nick Newcomer Published in the United States of America by in (an imprint of IGI Global) 701 E Chocolate Avenue Hershey PA 17033 Tel: 717-533-8845 Fax: 717-533-8661 E-mail: cust@igi-global.com Web site: http://www.igi-global.com Copyright © 2011 by IGI Global All rights reserved No part of this publication may be reproduced, stored or distributed in any form or by any means, electronic or mechanical, including photocopying, without written permission from the publisher Product or company names used in this set are for identification purposes only Inclusion of the names of the products or companies does not indicate a claim of ownership by IGI Global of the trademark or registered trademark Library of Congress Cataloging-in-Publication Data Cloud, grid and high performance computing: emerging applications / Emmanuel Udoh, editor p cm Includes bibliographical references and index Summary: “This book offers new and established perspectives on architectures, services and the resulting impact of emerging computing technologies, including investigation of practical and theoretical issues in the related fields of grid, cloud, and high performance computing” Provided by publisher ISBN 978-1-60960-603-9 (hardcover) ISBN 978-1-60960-604-6 (ebook) Cloud computing Computational grids (Computer systems) Software architecture Computer software Development I Udoh, Emmanuel, 1960QA76.585.C586 2011 004.67’8 dc22 2011013282 British Cataloguing in Publication Data A Cataloguing in Publication record for this book is available from the British Library All work contributed to this book is new, previously-unpublished material The views expressed in this book are those of the authors, but not necessarily of the publisher Table of Contents Preface xvi Section Introduction Chapter Supercomputers in Grids Michael M Resch, University of Stuttgart, Germany Edgar Gabriel, University of Houston, USA Chapter Porting HPC Applications to Grids and Clouds 10 Wolfgang Gentzsch, Independent HPC, Grid, and Cloud Consultant, Germany Chapter Grid-Enabling Applications with JGRIM 39 Cristian Mateos, ISISTAN - UNCPBA, Argentina Alejandro Zunino, ISISTAN - UNCPBA, Argentina Marcelo Campo, ISISTAN - UNCPBA, Argentina Section Scheduling Chapter Moldable Job Allocation for Handling Resource Fragmentation in Computational Grid 58 Kuo-Chan Huang, National Taichung University of Education, Taiwan Po-Chi Shih, National Tsing Hua University, Taiwan Yeh-Ching Chung, National Tsing Hua University, Taiwan Chapter Speculative Scheduling of Parameter Sweep Applications Using Job Behaviour Descriptions 72 Attila Ulbert, tvưs Loránd University, Hungary László Csaba Lőrincz, tvưs Loránd University, Hungary Tamás Kozsik, Eötvös Loránd University, Hungary Zoltán Horváth, Eötvös Loránd University, Hungary Chapter A Security Prioritized Computational Grid Scheduling Model: An Analysis 90 Rekha Kashyap, Jawaharlal Nehru University, India Deo Prakash Vidyarthi, Jawaharlal Nehru University, India Chapter A Replica Based Co-Scheduler (RBS) for Fault Tolerant Computational Grid 101 Zahid Raza, Jawaharlal Nehru University, India Deo Prakash Vidyarthi, Jawaharlal Nehru University, India Section Security Chapter A Policy-Based Security Framework for Privacy-Enhancing Data Access and Usage Control in Grids 118 Wolfgang Hommel, Leibniz Supercomputing Centre, Germany Chapter Adaptive Control of Redundant Task Execution for Dependable Volunteer Computing 135 Hong Wang, Tohoku University, Japan Yoshitomo Murata, Tohoku University, Japan Hiroyuki Takizawa, Tohoku University, Japan Hiroaki Kobayashi, Tohoku University, Japan Chapter 10 Publication and Protection of Sensitive Site Information in a Grid Infrastructure 155 Shreyas Cholia, Lawrence Berkeley National Laboratory, USA R Jefferson Porter, Lawrence Berkeley National Laboratory, USA Chapter 11 Federated PKI Authentication in Computing Grids: Past, Present, and Future 165 Massimiliano Pala, Dartmouth College, USA Shreyas Cholia, Lawrence Berkeley National Laboratory, USA Scott A Rea, DigiCert Inc., USA Sean W Smith, Dartmouth College, USA Chapter 12 Identifying Secure Mobile Grid Use Cases 180 David G Rosado, University of Castilla-La Mancha, Spain Eduardo Fernández-Medina, University of Castilla-La Mancha, Spain Javier López, University of Málaga, Spain Mario Piattini, University of Castilla-La Mancha, Spain Chapter 13 Trusted Data Management for Grid-Based Medical Applications 208 Guido J van ‘t Noordende, University of Amsterdam, The Netherlands Silvia D Olabarriaga, Academic Medical Center - Amsterdam, The Netherlands Matthijs R Koot, University of Amsterdam, The Netherlands Cees T.A.M de Laat, University of Amsterdam, The Netherlands Section Applications Chapter 14 Large-Scale Co-Phylogenetic Analysis on the Grid 222 Heinz Stockinger, Swiss Institute of Bioinformatics, Switzerland Alexander F Auch, University of Tübingen, Germany Markus Göker, University of Tübingen, Germany Jan Meier-Kolthoff, University of Tübingen, Germany Alexandros Stamatakis, Ludwig-Maximilians-University Munich, Germany Chapter 15 Persistence and Communication State Transfer in an Asynchronous Pipe Mechanism 238 Philip Chan, Monash University, Australia David Abramson, Monash University, Australia Chapter 16 Self-Configuration and Administration of Wireless Grids 255 Ashish Agarwal, Carnegie Mellon University, USA Amar Gupta, University of Arizona, USA Chapter 17 Push-Based Prefetching in Remote Memory Sharing System 269 Rui Chu, National University of Defense Technology, China Nong Xiao, National University of Defense Technology, China Xicheng Lu, National University of Defense Technology, China Chapter 18 Distributed Dynamic Load Balancing in P2P Grid Systems 284 You-Fu Yu, National Taichung University, Taiwan, ROC Po-Jung Huang, National Taichung University, Taiwan, ROC Kuan-Chou Lai, National Taichung University, Taiwan, ROC Chapter 19 An Ontology-Based P2P Network for Semantic Search 299 Tao Gu, University of Southern Denmark, Denmark Daqing Zhang, Institut Telecom SudParis, France Hung Keng Pung, National University of Singapore, Singapore Chapter 20 FH-MAC: A Multi-Channel Hybrid MAC Protocol for Wireless Mesh Networks 313 Djamel Tandjaoui, Center of Research on Scientific and Technical Information, Algeria Messaoud Doudou, University of Science and Technology Houari Boumediène, Algeria Imed Romdhani, Napier University School of Computing, UK Chapter 21 A Decentralized Directory Service for Peer-to-Peer-Based Telephony 330 Fabian Stäber, Siemens Corporate Technology, Germany Gerald Kunzmann, Technische Universität München, Germany Jörg P Müller, Clausthal University of Technology, Germany Compilation of References 345 About the Contributors 374 Index 385 Detailed Table of Contents Preface xvi Section Introduction Chapter Supercomputers in Grids Michael M Resch, University of Stuttgart, Germany Edgar Gabriel, University of Houston, USA This article describes the state of the art in using supercomputers in Grids It focuses on various approaches in Grid computing that either aim to replace supercomputing or integrate supercomputers in existing Grid environments We further point out the limitations to Grid approaches when it comes to supercomputing We also point out the potential of supercomputers in Grids for economic usage For this, we describe a public-private partnership in which this approach has been employed for more than 10 years By giving such an overview we aim at better understanding the role of supercomputers and Grids and their interaction Chapter Porting HPC Applications to Grids and Clouds 10 Wolfgang Gentzsch, Independent HPC, Grid, and Cloud Consultant, Germany A Grid enables remote, secure access to a set of distributed, networked computing and data resources Clouds are a natural complement to Grids towards the provisioning of IT as a service To “Grid-enable” applications, users have to cope with: complexity of Grid infrastructure; heterogeneous compute and data nodes; wide spectrum of Grid middleware tools and services; the e-science application architectures, algorithms and programs For clouds, on the other hand, users don’t have many possibilities to adjust their application to an underlying cloud architecture, because of its transparency to the user Therefore, the aim of this chapter is to guide users through the important stages of implementing HPC applications on Grid and cloud infrastructures, together with a discussion of important challenges and their potential solutions As a case study for Grids, we present the Distributed European Infrastructure for Supercomputing Applications (DEISA) and describe the DEISA Extreme Computing Initiative (DECI) for porting and running scientific grand challenge applications on the DEISA Grid For clouds, we present several case studies of HPC applications running on Amazon’s Elastic Compute Cloud EC2 and its recent Cluster Compute Instances for HPC This chapter concludes with the author’s top ten rules of building sustainable Grid and cloud e-infrastructures Chapter Grid-Enabling Applications with JGRIM 39 Cristian Mateos, ISISTAN - UNCPBA, Argentina Alejandro Zunino, ISISTAN - UNCPBA, Argentina Marcelo Campo, ISISTAN - UNCPBA, Argentina The development of massively distributed applications with enormous demands for computing power, memory, storage and bandwidth is now possible with the Grid Despite these advances, building Grid applications is still very difficult We present JGRIM, an approach to easily gridify Java applications by separating functional and Grid concerns in the application code, and report evaluations of its benefits with respect to related approaches The results indicate that JGRIM simplifies the process of porting applications to the Grid, and the Grid code obtained from this process performs in a very competitive way compared to the code resulting from using similar tools Section Scheduling Chapter Moldable Job Allocation for Handling Resource Fragmentation in Computational Grid 58 Kuo-Chan Huang, National Taichung University of Education, Taiwan Po-Chi Shih, National Tsing Hua University, Taiwan Yeh-Ching Chung, National Tsing Hua University, Taiwan In a computational Grid environment, a common practice is to try to allocate an entire parallel job onto a single participating site Sometimes a parallel job, upon its submission, cannot fit in any single site due to the occupation of some resources by running jobs How the job scheduler handles such situations is an important issue which has the potential to further improve the utilization of Grid resources, as well as the performance of parallel jobs This paper adopts moldable job allocation policies to deal with such situations in a heterogeneous computational Grid environment The proposed policies are evaluated through a series of simulations using real workload traces The moldable job allocation policies are also compared to the multi-site co-allocation policy, which is another approach usually used to deal with the resource fragmentation issue The results indicate that the proposed moldable job allocation policies can further improve the system performance of a heterogeneous computational Grid significantly Chapter Speculative Scheduling of Parameter Sweep Applications Using Job Behaviour Descriptions 72 Attila Ulbert, tvưs Loránd University, Hungary László Csaba Lőrincz, tvưs Loránd University, Hungary Tamás Kozsik, Eötvös Loránd University, Hungary Zoltán Horváth, Eötvös Loránd University, Hungary The execution of data intensive Grid applications raises several questions regarding job scheduling, data migration, and replication This paper presents new scheduling algorithms using more sophisticated job behaviour descriptions that allow estimating job completion times more precisely thus improving scheduling decisions Three approaches of providing input to the decision procedure are discussed: a) single job description, b) multiple job descriptions, and c) multiple job descriptions with mutation The proposed Grid middleware components (1) monitor the execution of jobs and gather resource access information, (2) analyse the compiled information and generate a description of the behaviour of the job, (3) refine the already existing job description, and (4) use the refined behaviour description to schedule the submitted jobs Chapter A Security Prioritized Computational Grid Scheduling Model: An Analysis 90 Rekha Kashyap, Jawaharlal Nehru University, India Deo Prakash Vidyarthi, Jawaharlal Nehru University, India Grid supports heterogeneities of resources in terms of security and computational power Applications with stringent security requirement introduce challenging concerns when executed on the grid resources Though grid scheduler considers the computational heterogeneity while making scheduling decisions, little is done to address their security heterogeneity This work proposes a security aware computational grid scheduling model, which schedules the tasks taking into account both kinds of heterogeneities The approach is known as Security Prioritized MinMin (SPMinMin) Comparing it with one of the widely used grid scheduling algorithm MinMin (secured) shows that SPMinMin performs better and sometimes behaves similar to MinMin under all possible situations in terms of makespan and system utilization Chapter A Replica Based Co-Scheduler (RBS) for Fault Tolerant Computational Grid 101 Zahid Raza, Jawaharlal Nehru University, India Deo Prakash Vidyarthi, Jawaharlal Nehru University, India Grid is a parallel and distributed computing network system comprising of heterogeneous computing resources spread over multiple administrative domains that offers high throughput computing Since the Grid operates at a large scale, there is always a possibility of failure ranging from hardware to software The penalty paid of these failures may be on a very large scale System needs to be tolerant to various possible failures which, in spite of many precautions, are bound to happen Replication is a strategy often used to introduce fault tolerance in the system to ensure successful execution of the job, even when some of the computational resources fail Though replication incurs a heavy cost, a selective degree of ... researchers, and professionals abreast of advances in the cloud, Grid, and high performance computing, this book series Cloud, Grid, and High Performance Computing: Emerging Applications will provide coverage... Introduction, provides an overview of supercomputing and the porting of applications to Grid and cloud environments Cloud, Grid and high performance computing are firmly dependent on the information... private clouds will persist until public clouds mature and garner corporate trust The embrace of cloud computing is impacting the adoption of Grid technology The perceived usefulness of Grid computing