ADVANCES IN GRID COMPUTING ppt

ADVANCES IN GRID COMPUTING Edited by Zoran ConstanƟ nescu Advances in Grid Computing Edited by Zoran Constantinescu Published by InTech Janeza Trdine 9, 51000 Rijeka, Croatia Copyright © 2011 InTech All chapters are Open Access articles distributed under the Creative Commons Non Commercial Share Alike Attribution 3.0 license, which permits to copy, distribute, transmit, and adapt the work in any medium, so long as the original work is properly cited. After this work has been published by InTech, authors have the right to republish it, in whole or part, in any publication of which they are the author, and to make other personal use of the work. Any republication, referencing or personal use of the work must explicitly identify the original source. Statements and opinions expressed in the chapters are these of the individual contributors and not necessarily those of the editors or publisher. No responsibility is accepted for the accuracy of information contained in the published articles. The publisher assumes no responsibility for any damage or injury to persons or property arising out of the use of any materials, instructions, methods or ideas contained in the book. Publishing Process Manager Katarina Lovrecic Technical Editor Teodora Smiljanic Cover Designer Martina Sirotic Image Copyright DrHitch, 2010. Used under license from Shutterstock.com First published February, 2011 Printed in India A free online edition of this book is available at www.intechopen.com Additional hard copies can be obtained from orders@intechweb.org Advances in Grid Computing, Edited by Zoran Constantinescu p. cm. ISBN 978-953-307-301-9 free online editions of InTech Books and Journals can be found at www.intechopen.com Part 1 Chapter 1 Chapter 2 Chapter 3 Chapter 4 Chapter 5 Chapter 6 Part 2 Chapter 7 Preface IX Resource and Data Management 1 Application of Discrete Particle Swarm Optimization for Grid Task Scheduling Problem 3 Ruey-Maw Chen A Framework for Problem- Specific QoS Based Scheduling in Grids 19 Mohamed Wahib, Asim Munawar, Masaharu Munetomo and Kiyoshi Akama Grid-JQA: A QoS Guided Scheduling Algorithm for Grid Computing 29 Leyli Mohammad Khanli and Saeed Kargar Autonomic Network-Aware Metascheduling for Grids: A Comprehensive Evaluation 49 Agustín C. Caminero, Omer Rana, Blanca Caminero and Carmen Carrión Quantum Encrypted Data Transfers in GRID 73 M. Dima, M. Dulea, A. Dima, M. Stoica and M. Udrea Data Consolidation and Information Aggregation in Grid Networks 95 Panagiotis Kokkinos and Emmanouel Varvarigos Grid Architectures and Development 119 A GPU Accelerated High Performance Cloud Computing Infrastructure for Grid Computing Based Virtual Environmental Laboratory 121 Giulio Giunta, Raffaele Montella, Giuliano Laccetti, Florin Isaila and Javier García Blas Contents Contents VI Using Open Source Desktop Grids in Scientific Computing and Visualization 147 Zoran Constantinescu and Monica Vladoiu Security in the Development Process of Mobile Grid Systems 173 David G. Rosado, Eduardo Fernández-Medina and Javier López Grid Enabled Applications 199 Grid Computing for Artificial Intelligence 201 Yuya Dan Grid Computing for Fusion Research 215 Francisco Castejón and Antonio Gómez-Iglesias A Grid Enabled Framework for Ubiquitous Healthcare Service Provisioning 229 Oludayo, O., Olugbara, Sunday, O. Ojo, and Mathew, O. Adigun The Porting of Wargi-DSS to Grid Computing Environment for Drought Plans in Complex Water Systems 253 Andrea Sulis, Valeria Ardizzone, Emilio Giorgio and Giovanni M. Sechi Chapter 8 Chapter 9 Part 3 Chapter 10 Chapter 11 Chapter 12 Chapter 13 Preface During the last decades we have been experiencing the historic evolution of Informa- tion and Communication Technology’s integration into our society to the point that many times people use it transparently. As we become able to do more and more with our advanced technologies, and as we hide them and their complexities completely from their users, we will have accomplished the envisioned “magic” desideratum that any advanced technology must fulfi ll in Arthur Clarke’s vision. Internet has enabled a major breakthrough, not so long ago, when its standards and technologies provided for near-universal connectivity, broad access to content, and, consequently, for a new model for science, engineering, education, business, and life itself. That development has been extraordinary in many respects, and, the Grid is expected to continue this momentous evolution toward fulfi lling of Licklider’s vision of man-computer symbio- sis and intergalactic network that enable people and computers to cooperate in making decisions and controlling complex situations without infl exible dependence on predetermined programs. Grid Computing is a model of distributed computing that uses geographically and administratively distinct resources that can be reached over the network: processing power, storage capacity, specifi c data, input and output devices, etc. Foster’s canoni- cal defi nition of Grid states that it is a system that coordinates distributed resources using standard, open, general-purpose protocols and interfaces to deliver nontrivial qualities of ser- vice. In grid computing, individual users can access computers and data transparently, without having to consider location, operating system, account administration, and other details, which are abstracted from the users. Grid computing aims to achieve a secured, controlled and fl exible sharing of virtualized resources among various dy- namically created virtual organizations. However, the construction of an application that may benefi t from advantages of grid computing, i.e. faster execution speed, con- necting of geographically separated resources, interoperation of software, and so on, typically requires the installation of complex supporting software, and, moreover, an in-depth knowledge of how this software works. This book approaches grid computing from the perspective of the latest achievements in the fi eld, providing an insight into the current research trends and advances, and presents a large range of innovative research in this fi eld. The topics covered in this book include resource and data management, grid architectures and development, and X Preface grid-enabled applications. The book consists of 13 chapters, which are grouped into three sections as follows. First section, entitled Resource and Data Management, consists of chapters 1 to 6, and discusses two main aspects of grid computing: the availabil- ity of resources for jobs (resource management), and the availability of data to the jobs (data management). New ideas employing heuristic methods from swarm intelligence or genetic algorithm, and quantum encryption are introduced. For instance, Chapter 1 focuses on applying discrete particle swarm optimization algorithm, a swarm intel- ligence inspired technique, to solve the task scheduling problem in grid computing. Chapter 2 discusses the use of application specifi c Quality of Service (QoS) param- eters for resource management, and proposes a framework for task scheduling using a multi objective genetic algorithm. Chapter 3 proposes a new QoS guided scheduling algorithm. Chapter 4 introduces an autonomic network-aware metascheduling archi- tecture, evaluating the benefi ts of taking the network into account when performing metascheduling, along with the need to react autonomically to changes in the system. Chapter 5 presents an a empt to use quantum encryption for data transmission in the grid. Chapter 6 proposes a number of data consolidation and information aggregation techniques, and evaluates by simulation the improvements in the reduction of conges- tion and information exchanged. The second section, named Grid Architectures and Development, includes chapters 7 to 9, and addresses some aspects of grid computing that regard architecture and develop- ment. Chapter 7 describes the development of a virtual laboratory for environmental applications, based on grid computing, cloud computing and GPU computing compo- nents. Chapter 8 presents the architecture of an open source, heterogeneous, desktop grid computing system, together with some examples of using it in the fi elds of scien- tifi c computing and visualization. Chapter 9 defi nes a systematic development process for grid systems that supports the participation of mobile nodes, and it incorporates security aspects from the earliest stages of development. Grid Enabled Applications, the last section of this book, includes chapters 10 to 13, and provides a diverse range of applications for grid computing, including a possible hu- man grid computing system, a simulation of the fusion reaction, ubiquitous healthcare service provisioning and complex water systems. Chapter 10 introduces the idea of us- ing grid computing in artifi cial intelligence, namely for thinking routines for the next move problems in the game of shogi (Japanese chess), and presents the possibility of the human Grid computing, which assists the position evaluation function with human intuition. Chapter 11 presents the application of grid computing in fusion research, the problems involved in porting fusion applications to the grid towards the fi nal quest of a numerical fusion reactor. Chapter 12 describes the eff ort to design and evaluate a grid enabled framework for ubiquitous healthcare service provisioning, by integrat- ing diff erent emerging technologies like telemedicine, wireless body area network and wireless utility grid computing technologies, to address the challenges of conventional healthcare system. Chapter 13 presents grid computing as a promising approach for scaled-up simulation analysis of complex water system with high uncertainty on hy- drological series. [...]... resources in grid environment are considered in this investigation 2 The task scheduling problem in grid computing There are different grid task scheduling problems exist including homogeneous and heterogeneous architectures This section gives a class of task scheduling problem in homogeneous grid Definition, limitation and objective of a grid computing system are presented The introduced grid task scheduling... for a different discipline (i.e SOA) It is of no-awkwardness to use a mechanism that was originally defined in SOA (Service Oriented Architecture) service workflows to be used in grid computing As grid computing and SOA have many tangency points And this point in particular could be considered a convergence point between grid computing and SOA At the first glance, scheduling tasks in such an environment... 1957 4276 3562 5156 16 Advances in Grid Computing 7 Summary This study introduces the discrete PSO algorithm for solving task -grid assignment problem in a distributed grid environment Experiment results indicate that the discrete version of PSO combining simulated annealing is effective for solving task -grid assignment problems However, more complicated cases can be considered in- depth, such as more... grid computing To enhance the performance of the applied DPSO, additional heuristic was introduced to solve the investigated scheduling problem in grid Restated, simulated annealing (SA) algorithm was incorporated into DPSO to solve task assignment problem in grid environment Moreover, the resulting change in position is defined by roulette wheel selection rule rather than the used rule in [Kennedy... The proposed discrete PSO combined with SA 12 Advances in Grid Computing 5.1 DPSO encoding representation Encoding the task assignment problem in grid into the position vector of particle is necessary Hence, encoding is illustrated by an example as follows For example, there are 5 tasks to be distributed to 3 grids; the initial velocity for particle h (Vhij) is Task \ Grid 1 2 3 4 5 1 -1.2 1.1 1.2... for solving different scheduling application problems including production scheduling [Watts & Strogatz, 1998], project scheduling [Chen, 2010], call center scheduling [chiu et al., 2009], and others [Behnamian et al., 2010; Hei et al., 2009] In light of different algorithms studied, PSO is a promising and well-applied meta-heuristic approach in finding the optimal solutions of diverse scheduling problems... Simeonovova, 2002], control system [Fleming & Fonseca, 1993], resource-constrained scheduling problem [Chen, 2007] and grid computing There are many different types of scheduling problems such as real-time, job-shop, permutation flow-shop, project scheduling and other scheduling problems have been studied intensively However, in this work, the studied grid task scheduling problem is much more complex than... as resource scheduling according to some criteria The criteria are referred to as Quality of Service (QoS) attributes in grid computing context QoS in general are non-functional characters describing a process QoS attributes are divided into two main groups, namely objective QoS and subjective QoS Objective QoS attributes are used to specify performance parameters including timeliness, precision, accuracy,... than above stated classic task scheduling problems Restated, a grid application is regarded as a task scheduling problem involving tasks with inter-communication and distributed homogeneous or heterogeneous resources, and can be represented by a task interaction graph (TIG) Grid is a service for sharing computing power and data storage capacity over the Internet The grid systems outperform simple communication... adopted here by including the aggregator in a Vine portlet and adding it to the gridsphere portal Modifications were done to drop operators for individual tasks as mentioned earlier, associate the newly defined Qos attribute to any of the task types registered by the administrator and finally adapting the original JSP to work with the Adobe Flex GUI used in gridsphere 3.1 The aggregator include three basic . ADVANCES IN GRID COMPUTING Edited by Zoran ConstanƟ nescu Advances in Grid Computing Edited by Zoran Constantinescu Published by InTech Janeza Trdine 9, 51000 Rijeka, Croatia Copyright. resources in grid environment are considered in this investigation. 2. The task scheduling problem in grid computing There are different grid task scheduling problems exist including homogeneous. running on the grid. In grid computing, tasks are assigned among grid system [Salman, 2002]. The purpose of task scheduling in grid is to find optimal task-processor assignment and hence minimize