Service Oriented Storage System Grid

Service Oriented Storage System Grid

Yuhui Deng (Cranfield University, UK), Frank Zhigang Wang (Cranfield University, UK) and Na Helian (Metropolitan University, UK)
DOI: 10.4018/978-1-60566-184-1.ch013
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Abstract

Storage Grid is a new model for deploying and managing the heterogeneous, dynamic, large-scale, and geographically distributed storage resources. This chapter discusses the challenges and solutions involved in building a Service Oriented Storage (SOS) Grid. By wrapping the diverse storage resources into atomic Grid services and federating multiple atomic Grid services into composite services, the SOS Grid can tackle the heterogeneity and interoperability. Peer-to-peer philosophy and techniques are employed in the SOS Grid to eliminate the system bottleneck and single point of failure of the traditional centralized or hierarchical Grid architecture, while providing dynamicity and scalability. Because Grid service is not designed for critical and real-time applications, the SOS Grid adopts Grid service to glue the distributed and heterogeneous storage resources, while using binary code to transfer data. The proposed methods strike a good balance among the heterogeneity, interoperability, scalability and performance of the SOS Grid.
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Introduction

According to a new report from IDC (IDC white paper, 2007), 161 exabytes of digital information were created and copied in 2006. The growth will continue to increase exponentially. The amount of information in 2010 will surge more than six fold to 988 exabytes which amounts to a compound annual growth rate of 57%. About 70% of the digital information will be generated by individuals over the next three years. The data will be stored in a large number of data centers which are distributed across the Internet. The data centers may have completely heterogeneous operating systems, computer architectures, and IT infrastructures.

The explosive growth of data has been identified as the key driver to escalate storage requirements. There are two major technologies which impact the evolution of storage systems. The first one is parallel processing such as redundant arrays of inexpensive disks (RAID) (Gibson, et al, 1988). The second one is the influence of network technology on storage system architecture. Network based storage systems such as network attached storage (NAS) and storage area network (SAN) (Gibson and Meter, 2000; Morris and Truskowski, 2003) offer a robust and easy method to control and access large amounts of storage resources. However, the ever increasing amounts of data generated worldwide incur a significant impact on the storage systems we have today (Min, et al, 2005). It requires more sophisticated techniques and more flexible and reliable storage systems to store and manage the data (e.g. providing petabytes and even exabyte storage capacity, and aggregate bandwidth over 100 GB/s). Undoubtedly, NAS and SAN cannot meet the requirements. It is a big challenge to design an autonomous, dynamic, large-scale and scalable storage system which consolidates distributed and heterogeneous storage resources to satisfy both the bandwidth and storage capacity requirements.

A Grid is a flexible, secure, coordinated resource sharing among dynamic collections of individuals, institutions, and resources (Foster, et al, 2001). The objective is to virtualize resources including computers, networks, instruments and so on and allow users and applications to access the resources in a transparent manner. A Grid environment may consist of hundreds or even thousands of geographically distributed and heterogeneous resources to match the requirements imposed by all kinds of Grid applications. Grid computing has emerged as an important new field, distinguished from conventional distributed computing by its focus on large scale resource sharing and high performance orientation. Table 1 illustrates the characteristics of Grid and data storage.

Table 1.
Characteristics comparison of Grid and data storage
Grid CharacteristicsData Storage Characteristics
Large scale or global distribution     Worldwide
Dynamic coordination     Ever-increasing
Collaborative virtual organizationsRequire Interoperability
User transparentInvolve large quantity of heterogeneous storage resources
Secured communicationHigh security, privacy, and reliability

Key Terms in this Chapter

Storage Grid: Storage grid is a virtual organization which federates the geographically distributed and heterogeneous storage systems into a logical community with only minimal administrative requirements, while providing scalability and interoperability.

Web Service: Web service is defined by W3C as a software system designed to support interoperable machine to machine interaction over a network. A web service provides interfaces described by a machine-processable WSDL document, and other systems can interact with the service using SOAP messages.

Storage Service Composition: Storage service composition indicates combining available atomic storage services as composition service to meet the data requirements of complex applications.

Grid Service: A grid service is a stateful web service with an associated lifetime which provides a set of interfaces through which grid users may interact.

Storage Interoperability: Storage interoperability provides seamless resource consolidation and cooperation among a large number of heterogeneous storage resources by using standard interfaces.

Grid Scheduler: Grid scheduler is in charge of scheduling jobs or applications where resources are distributed across a large scale or multiple administrative domains.

Storage Management: Storage management indicates a virtualization method which is employed to maximize the overall resource utilization of the storage systems by intelligently allocating the available storage resources among the applications above it, thus guaranteeing on-demand storage requirements.

Storage Scalability: Storage scalability is the ability to provide satisfied capabilities including storage capacity, performance and fault tolerance when a storage system is increased in size in order to meet the data requirements.

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Editorial Advisory Board
Table of Contents
Foreword
Ruth E. Shaw
Preface
Emmanuel Udoh, Frank Zhigang Wang
Acknowledgment
Emmanuel Udoh
Chapter 1
Emmanuel Udoh, Frank Zhigang Wang, Vineet R. Khare
This chapter presents a historical record of the advent of Grid with a recourse to some basic definitions commonly accepted by most researchers. It... Sample PDF
Overview of Grid Computing
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Chapter 2
Eric Aubanel
The problem of load balancing parallel applications is particularly challenging on computational grids, since the characteristics of both the... Sample PDF
Resource-Aware Load Balancing of Parallel Applications
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Chapter 3
Enis Afgan, Purushotham Bangalore
Grid computing has emerged as the next generation computing platform. Because of the resource heterogeneity that exists in the grid environment... Sample PDF
Assisting Efficient Job Planning and Scheduling in the Grid
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Chapter 4
Kuo-Chan Huang, Po-Chi Shih, Yeh-Ching Chung
Most current grid environments are established through collaboration among a group of participating sites which volunteer to provide free computing... Sample PDF
Effective Resource Allocation and Job Scheduling Mechanisms for Load Sharing in a Computational Grid
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Chapter 5
Tevfik Kosar
As the data requirements of scientific distributed applications increase, the access to remote data becomes the main performance bottleneck for... Sample PDF
Data-Aware Distributed Batch Scheduling
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Chapter 6
Gianni Pucciani, Flavia Donno, Andrea Domenici, Heinz Stockinger
Data replication is a well-known technique used in distributed systems in order to improve fault tolerance and make data access faster. Several... Sample PDF
Consistency of Replicated Datasets in Grid Computing
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Chapter 7
Ming Wu, Xian-He Sun
Rapid advancement of communication technology has changed the landscape of computing. New models of computing, such as business-on-demand, Web... Sample PDF
Quality of Service of Grid Computing
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Chapter 8
QoS in Grid Computing  (pages 75-83)
Zhihui Du, Zhili Cheng, Xiaoying Wang, Chuang Lin
This chapter first summarizes popular terms of QoS related concepts and technologies in grid computing, including SLA, End-to-End QoS Provision and... Sample PDF
QoS in Grid Computing
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Chapter 9
Kris Bubendorfer, Ben Palmer, Ian Welch
A Grid resource broker is the arbiter for access to a Grid’s computational resources and therefore its performance and functionality has a... Sample PDF
Trust and Privacy in Grid Resource Auctions
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Chapter 10
Sandro Fiore, Alessandro Negro, Salvatore Vadacca, Massimo Cafaro, Giovanni Aloisio, Roberto Barbera
Grid computing is an emerging and enabling technology allowing organizations to easily share, integrate and manage resources in a distributed... Sample PDF
An Architectural Overview of the GRelC Data Access Service
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Chapter 11
Man Wang, Zhihui Du, Zhili Cheng
Resource Management System (RMS), which manages the Grid resources and matches the applications’ requests to the proper resources, is one of the... Sample PDF
Adaptive Resource Management in Grid Environment
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Chapter 12
Vineet R. Khare, Frank Zhigang Wang
The need for a dynamic and scalable expansion of the grid infrastructure and resources and other scalability issues in terms of execution efficiency... Sample PDF
Bio-Inspired Grid Resource Management
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Chapter 13
Yuhui Deng, Frank Zhigang Wang, Na Helian
Storage Grid is a new model for deploying and managing the heterogeneous, dynamic, large-scale, and geographically distributed storage resources.... Sample PDF
Service Oriented Storage System Grid
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Chapter 14
Dominic Cherry, Maozhen Li, Man Qi
This chapter presents MediaGrid, a distributed storage system for archiving broadcast media contents. MediaGrid utilizes storage resources donated... Sample PDF
A Distributed Storage System for Archiving Broadcast Media Content
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Chapter 15
Maozhen Li, Man Qi, Bin Yu
The computational grid is rapidly evolving into a service-oriented computing infrastructure that facilitates resource sharing and large-scale... Sample PDF
Service Discovery with Rough Sets
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Chapter 16
Irfan Habib, Ashiq Anjum, Richard McClatchey
Due to some barriers to adoption we have not seen a proliferation of Grid Computing technologies throughout e-Science or other domains. This chapter... Sample PDF
On the Pervasive Adoption of Grid Technologies: A Grid Operating System
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Chapter 17
Kurt Vanmechelen, Jan Broeckhove, Wim Depoorter, Khalid Abdelkader
As grid computing technology moves further up the adoption curve, the issues of dealing with conflicting user requirements formulated by different... Sample PDF
Pricing Computational Resources in Grid Economies
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Chapter 18
Rosario M. Piro
Large, geographically distributed and heterogeneous computing infrastructures, such as the Grid, often span multiple organizations and... Sample PDF
Resource Usage Accounting in Grid Computing
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Chapter 19
Frans Arickx, Jan Broeckhove, Peter Hellinckx, David Dewolfs, Kurt Vanmechelen
Quantum structure or scattering calculations often belong to a class of computational problems involving the aggregation of a set of matrices... Sample PDF
Grid-Based Nuclear Physics Applications
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Chapter 20
Gabriel Aparicio, Fernando Blanco, Ignacio Blanquer, César Bonavides, Juan Luis Chaves, Miguel Embid, Álvaro Hernández
In the last years an increasing demand for Grid Infrastructures has resulted in several international collaborations. This is the case of the EELA... Sample PDF
Developing Biomedical Applications in the Framework of EELA
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Chapter 21
Gerald Schaefer, Roger Tait
Efficient approaches to computationally intensive image processing tasks are currently highly sought after. In this chapter, the authors show how a... Sample PDF
Distributed Image Processing on a Blackboard System
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Chapter 22
Daniele Andreotti, Armando Fella, Eleonora Luppi
The BaBar experiment uses data since 1999 in examining the violation of charge and parity (CP) symmetry in the field of high energy physics. This... Sample PDF
Simulated Events Production on the Grid for the BaBar Experiment
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Chapter 23
Diego Liberati
A framework is proposed that creates, uses, and communicates information, whose organizational dynamics allows performing a distributed cooperative... Sample PDF
A Framework for Semantic Grid in E-Science
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Chapter 24
Roberto Barbera, Valeria Ardizzone, Leandro Ciuffo
The Grid INFN virtual Laboratory for Dissemination Activities (GILDA) is a fully working Grid test-bed devoted to training and dissemination... Sample PDF
Grid INFN Virtual Laboratory for Dissemination Activities (GILDA)
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Chapter 25
Dirk Gorissen, Tom Dhaene, Piet Demeester, Jan Broeckhove
The simulation and optimization of complex systems is a very time consuming and computationally intensive task. Therefore, global surrogate modeling... Sample PDF
Grid Enabled Surrogate Modeling
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Chapter 26
Patrik Skogster
Grid computing is becoming as essential part of different business analysis. In traditional business computing infrastructures data transfer occurs... Sample PDF
GIS Grids and the Business Use of GIS Data
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Chapter 27
Gokop Goteng, Ashutosh Tiwari, Rajkumar Roy
The emerging grid technology provides a secured platform for multidisciplinary experts in the security intelligence profession to collaborate and... Sample PDF
Grid Computing: Combating Global Terrorism with the World Wide Grid
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Chapter 28
Salvatore Scifo
This chapter focuses on the efforts to design and develop a standard pure Java API to access the metadata service of the EGEE Grid middleware, and... Sample PDF
Accessing Grid Metadata through a Web Interface
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Chapter 29
Jyotsna Sharma
Efforts in Grid Computing, both in academia and industry, continue to grow rapidly worldwide for research, scientific and commercial purposes.... Sample PDF
Grid Computing Initiatives in India
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Chapter 30
Hai Jin, Li Qi, Jie Dai, Yaqin Luo
A grid system is usually composed of thousands of nodes which are broadly distributed in different virtual organizations. Owing to geographical... Sample PDF
Dynamic Maintenance in ChinaGrid Support Platform
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