- •Cloud Computing
- •Foreword
- •Preface
- •Introduction
- •Expected Audience
- •Book Overview
- •Part 1: Cloud Base
- •Part 2: Cloud Seeding
- •Part 3: Cloud Breaks
- •Part 4: Cloud Feedback
- •Contents
- •1.1 Introduction
- •1.1.1 Cloud Services and Enabling Technologies
- •1.2 Virtualization Technology
- •1.2.1 Virtual Machines
- •1.2.2 Virtualization Platforms
- •1.2.3 Virtual Infrastructure Management
- •1.2.4 Cloud Infrastructure Manager
- •1.3 The MapReduce System
- •1.3.1 Hadoop MapReduce Overview
- •1.4 Web Services
- •1.4.1 RPC (Remote Procedure Call)
- •1.4.2 SOA (Service-Oriented Architecture)
- •1.4.3 REST (Representative State Transfer)
- •1.4.4 Mashup
- •1.4.5 Web Services in Practice
- •1.5 Conclusions
- •References
- •2.1 Introduction
- •2.2 Background and Related Work
- •2.3 Taxonomy of Cloud Computing
- •2.3.1 Cloud Architecture
- •2.3.1.1 Services and Modes of Cloud Computing
- •Software-as-a-Service (SaaS)
- •Platform-as-a-Service (PaaS)
- •Hardware-as-a-Service (HaaS)
- •Infrastructure-as-a-Service (IaaS)
- •2.3.2 Virtualization Management
- •2.3.3 Core Services
- •2.3.3.1 Discovery and Replication
- •2.3.3.2 Load Balancing
- •2.3.3.3 Resource Management
- •2.3.4 Data Governance
- •2.3.4.1 Interoperability
- •2.3.4.2 Data Migration
- •2.3.5 Management Services
- •2.3.5.1 Deployment and Configuration
- •2.3.5.2 Monitoring and Reporting
- •2.3.5.3 Service-Level Agreements (SLAs) Management
- •2.3.5.4 Metering and Billing
- •2.3.5.5 Provisioning
- •2.3.6 Security
- •2.3.6.1 Encryption/Decryption
- •2.3.6.2 Privacy and Federated Identity
- •2.3.6.3 Authorization and Authentication
- •2.3.7 Fault Tolerance
- •2.4 Classification and Comparison between Cloud Computing Ecosystems
- •2.5 Findings
- •2.5.2 Cloud Computing PaaS and SaaS Provider
- •2.5.3 Open Source Based Cloud Computing Services
- •2.6 Comments on Issues and Opportunities
- •2.7 Conclusions
- •References
- •3.1 Introduction
- •3.2 Scientific Workflows and e-Science
- •3.2.1 Scientific Workflows
- •3.2.2 Scientific Workflow Management Systems
- •3.2.3 Important Aspects of In Silico Experiments
- •3.3 A Taxonomy for Cloud Computing
- •3.3.1 Business Model
- •3.3.2 Privacy
- •3.3.3 Pricing
- •3.3.4 Architecture
- •3.3.5 Technology Infrastructure
- •3.3.6 Access
- •3.3.7 Standards
- •3.3.8 Orientation
- •3.5 Taxonomies for Cloud Computing
- •3.6 Conclusions and Final Remarks
- •References
- •4.1 Introduction
- •4.2 Cloud and Grid: A Comparison
- •4.2.1 A Retrospective View
- •4.2.2 Comparison from the Viewpoint of System
- •4.2.3 Comparison from the Viewpoint of Users
- •4.2.4 A Summary
- •4.3 Examining Cloud Computing from the CSCW Perspective
- •4.3.1 CSCW Findings
- •4.3.2 The Anatomy of Cloud Computing
- •4.3.2.1 Security and Privacy
- •4.3.2.2 Data and/or Vendor Lock-In
- •4.3.2.3 Service Availability/Reliability
- •4.4 Conclusions
- •References
- •5.1 Overview – Cloud Standards – What and Why?
- •5.2 Deep Dive: Interoperability Standards
- •5.2.1 Purpose, Expectations and Challenges
- •5.2.2 Initiatives – Focus, Sponsors and Status
- •5.2.3 Market Adoption
- •5.2.4 Gaps/Areas of Improvement
- •5.3 Deep Dive: Security Standards
- •5.3.1 Purpose, Expectations and Challenges
- •5.3.2 Initiatives – Focus, Sponsors and Status
- •5.3.3 Market Adoption
- •5.3.4 Gaps/Areas of Improvement
- •5.4 Deep Dive: Portability Standards
- •5.4.1 Purpose, Expectations and Challenges
- •5.4.2 Initiatives – Focus, Sponsors and Status
- •5.4.3 Market Adoption
- •5.4.4 Gaps/Areas of Improvement
- •5.5.1 Purpose, Expectations and Challenges
- •5.5.2 Initiatives – Focus, Sponsors and Status
- •5.5.3 Market Adoption
- •5.5.4 Gaps/Areas of Improvement
- •5.6 Deep Dive: Other Key Standards
- •5.6.1 Initiatives – Focus, Sponsors and Status
- •5.7 Closing Notes
- •References
- •6.1 Introduction and Motivation
- •6.2 Cloud@Home Overview
- •6.2.1 Issues, Challenges, and Open Problems
- •6.2.2 Basic Architecture
- •6.2.2.1 Software Environment
- •6.2.2.2 Software Infrastructure
- •6.2.2.3 Software Kernel
- •6.2.2.4 Firmware/Hardware
- •6.2.3 Application Scenarios
- •6.3 Cloud@Home Core Structure
- •6.3.1 Management Subsystem
- •6.3.2 Resource Subsystem
- •6.4 Conclusions
- •References
- •7.1 Introduction
- •7.2 MapReduce
- •7.3 P2P-MapReduce
- •7.3.1 Architecture
- •7.3.2 Implementation
- •7.3.2.1 Basic Mechanisms
- •Resource Discovery
- •Network Maintenance
- •Job Submission and Failure Recovery
- •7.3.2.2 State Diagram and Software Modules
- •7.3.3 Evaluation
- •7.4 Conclusions
- •References
- •8.1 Introduction
- •8.2 The Cloud Evolution
- •8.3 Improved Network Support for Cloud Computing
- •8.3.1 Why the Internet is Not Enough?
- •8.3.2 Transparent Optical Networks for Cloud Applications: The Dedicated Bandwidth Paradigm
- •8.4 Architecture and Implementation Details
- •8.4.1 Traffic Management and Control Plane Facilities
- •8.4.2 Service Plane and Interfaces
- •8.4.2.1 Providing Network Services to Cloud-Computing Infrastructures
- •8.4.2.2 The Cloud Operating System–Network Interface
- •8.5.1 The Prototype Details
- •8.5.1.1 The Underlying Network Infrastructure
- •8.5.1.2 The Prototype Cloud Network Control Logic and its Services
- •8.5.2 Performance Evaluation and Results Discussion
- •8.6 Related Work
- •8.7 Conclusions
- •References
- •9.1 Introduction
- •9.2 Overview of YML
- •9.3 Design and Implementation of YML-PC
- •9.3.1 Concept Stack of Cloud Platform
- •9.3.2 Design of YML-PC
- •9.3.3 Core Design and Implementation of YML-PC
- •9.4 Primary Experiments on YML-PC
- •9.4.1 YML-PC Can Be Scaled Up Very Easily
- •9.4.2 Data Persistence in YML-PC
- •9.4.3 Schedule Mechanism in YML-PC
- •9.5 Conclusion and Future Work
- •References
- •10.1 Introduction
- •10.2 Related Work
- •10.2.1 General View of Cloud Computing frameworks
- •10.2.2 Cloud Computing Middleware
- •10.3 Deploying Applications in the Cloud
- •10.3.1 Benchmarking the Cloud
- •10.3.2 The ProActive GCM Deployment
- •10.3.3 Technical Solutions for Deployment over Heterogeneous Infrastructures
- •10.3.3.1 Virtual Private Network (VPN)
- •10.3.3.2 Amazon Virtual Private Cloud (VPC)
- •10.3.3.3 Message Forwarding and Tunneling
- •10.3.4 Conclusion and Motivation for Mixing
- •10.4 Moving HPC Applications from Grids to Clouds
- •10.4.1 HPC on Heterogeneous Multi-Domain Platforms
- •10.4.2 The Hierarchical SPMD Concept and Multi-level Partitioning of Numerical Meshes
- •10.4.3 The GCM/ProActive-Based Lightweight Framework
- •10.4.4 Performance Evaluation
- •10.5 Dynamic Mixing of Clusters, Grids, and Clouds
- •10.5.1 The ProActive Resource Manager
- •10.5.2 Cloud Bursting: Managing Spike Demand
- •10.5.3 Cloud Seeding: Dealing with Heterogeneous Hardware and Private Data
- •10.6 Conclusion
- •References
- •11.1 Introduction
- •11.2 Background
- •11.2.1 ASKALON
- •11.2.2 Cloud Computing
- •11.3 Resource Management Architecture
- •11.3.1 Cloud Management
- •11.3.2 Image Catalog
- •11.3.3 Security
- •11.4 Evaluation
- •11.5 Related Work
- •11.6 Conclusions and Future Work
- •References
- •12.1 Introduction
- •12.2 Layered Peer-to-Peer Cloud Provisioning Architecture
- •12.4.1 Distributed Hash Tables
- •12.4.2 Designing Complex Services over DHTs
- •12.5 Cloud Peer Software Fabric: Design and Implementation
- •12.5.1 Overlay Construction
- •12.5.2 Multidimensional Query Indexing
- •12.5.3 Multidimensional Query Routing
- •12.6 Experiments and Evaluation
- •12.6.1 Cloud Peer Details
- •12.6.3 Test Application
- •12.6.4 Deployment of Test Services on Amazon EC2 Platform
- •12.7 Results and Discussions
- •12.8 Conclusions and Path Forward
- •References
- •13.1 Introduction
- •13.2 High-Throughput Science with the Nimrod Tools
- •13.2.1 The Nimrod Tool Family
- •13.2.2 Nimrod and the Grid
- •13.2.3 Scheduling in Nimrod
- •13.3 Extensions to Support Amazon’s Elastic Compute Cloud
- •13.3.1 The Nimrod Architecture
- •13.3.2 The EC2 Actuator
- •13.3.3 Additions to the Schedulers
- •13.4.1 Introduction and Background
- •13.4.2 Computational Requirements
- •13.4.3 The Experiment
- •13.4.4 Computational and Economic Results
- •13.4.5 Scientific Results
- •13.5 Conclusions
- •References
- •14.1 Using the Cloud
- •14.1.1 Overview
- •14.1.2 Background
- •14.1.3 Requirements and Obligations
- •14.1.3.1 Regional Laws
- •14.1.3.2 Industry Regulations
- •14.2 Cloud Compliance
- •14.2.1 Information Security Organization
- •14.2.2 Data Classification
- •14.2.2.1 Classifying Data and Systems
- •14.2.2.2 Specific Type of Data of Concern
- •14.2.2.3 Labeling
- •14.2.3 Access Control and Connectivity
- •14.2.3.1 Authentication and Authorization
- •14.2.3.2 Accounting and Auditing
- •14.2.3.3 Encrypting Data in Motion
- •14.2.3.4 Encrypting Data at Rest
- •14.2.4 Risk Assessments
- •14.2.4.1 Threat and Risk Assessments
- •14.2.4.2 Business Impact Assessments
- •14.2.4.3 Privacy Impact Assessments
- •14.2.5 Due Diligence and Provider Contract Requirements
- •14.2.5.1 ISO Certification
- •14.2.5.2 SAS 70 Type II
- •14.2.5.3 PCI PA DSS or Service Provider
- •14.2.5.4 Portability and Interoperability
- •14.2.5.5 Right to Audit
- •14.2.5.6 Service Level Agreements
- •14.2.6 Other Considerations
- •14.2.6.1 Disaster Recovery/Business Continuity
- •14.2.6.2 Governance Structure
- •14.2.6.3 Incident Response Plan
- •14.3 Conclusion
- •Bibliography
- •15.1.1 Location of Cloud Data and Applicable Laws
- •15.1.2 Data Concerns Within a European Context
- •15.1.3 Government Data
- •15.1.4 Trust
- •15.1.5 Interoperability and Standardization in Cloud Computing
- •15.1.6 Open Grid Forum’s (OGF) Production Grid Interoperability Working Group (PGI-WG) Charter
- •15.1.7.1 What will OCCI Provide?
- •15.1.7.2 Cloud Data Management Interface (CDMI)
- •15.1.7.3 How it Works
- •15.1.8 SDOs and their Involvement with Clouds
- •15.1.10 A Microsoft Cloud Interoperability Scenario
- •15.1.11 Opportunities for Public Authorities
- •15.1.12 Future Market Drivers and Challenges
- •15.1.13 Priorities Moving Forward
- •15.2 Conclusions
- •References
- •16.1 Introduction
- •16.2 Cloud Computing (‘The Cloud’)
- •16.3 Understanding Risks to Cloud Computing
- •16.3.1 Privacy Issues
- •16.3.2 Data Ownership and Content Disclosure Issues
- •16.3.3 Data Confidentiality
- •16.3.4 Data Location
- •16.3.5 Control Issues
- •16.3.6 Regulatory and Legislative Compliance
- •16.3.7 Forensic Evidence Issues
- •16.3.8 Auditing Issues
- •16.3.9 Business Continuity and Disaster Recovery Issues
- •16.3.10 Trust Issues
- •16.3.11 Security Policy Issues
- •16.3.12 Emerging Threats to Cloud Computing
- •16.4 Cloud Security Relationship Framework
- •16.4.1 Security Requirements in the Clouds
- •16.5 Conclusion
- •References
- •17.1 Introduction
- •17.1.1 What Is Security?
- •17.2 ISO 27002 Gap Analyses
- •17.2.1 Asset Management
- •17.2.2 Communications and Operations Management
- •17.2.4 Information Security Incident Management
- •17.2.5 Compliance
- •17.3 Security Recommendations
- •17.4 Case Studies
- •17.4.1 Private Cloud: Fortune 100 Company
- •17.4.2 Public Cloud: Amazon.com
- •17.5 Summary and Conclusion
- •References
- •18.1 Introduction
- •18.2 Decoupling Policy from Applications
- •18.2.1 Overlap of Concerns Between the PEP and PDP
- •18.2.2 Patterns for Binding PEPs to Services
- •18.2.3 Agents
- •18.2.4 Intermediaries
- •18.3 PEP Deployment Patterns in the Cloud
- •18.3.1 Software-as-a-Service Deployment
- •18.3.2 Platform-as-a-Service Deployment
- •18.3.3 Infrastructure-as-a-Service Deployment
- •18.3.4 Alternative Approaches to IaaS Policy Enforcement
- •18.3.5 Basic Web Application Security
- •18.3.6 VPN-Based Solutions
- •18.4 Challenges to Deploying PEPs in the Cloud
- •18.4.1 Performance Challenges in the Cloud
- •18.4.2 Strategies for Fault Tolerance
- •18.4.3 Strategies for Scalability
- •18.4.4 Clustering
- •18.4.5 Acceleration Strategies
- •18.4.5.1 Accelerating Message Processing
- •18.4.5.2 Acceleration of Cryptographic Operations
- •18.4.6 Transport Content Coding
- •18.4.7 Security Challenges in the Cloud
- •18.4.9 Binding PEPs and Applications
- •18.4.9.1 Intermediary Isolation
- •18.4.9.2 The Protected Application Stack
- •18.4.10 Authentication and Authorization
- •18.4.11 Clock Synchronization
- •18.4.12 Management Challenges in the Cloud
- •18.4.13 Audit, Logging, and Metrics
- •18.4.14 Repositories
- •18.4.15 Provisioning and Distribution
- •18.4.16 Policy Synchronization and Views
- •18.5 Conclusion
- •References
- •19.1 Introduction and Background
- •19.2 A Media Service Cloud for Traditional Broadcasting
- •19.2.1 Gridcast the PRISM Cloud 0.12
- •19.3 An On-demand Digital Media Cloud
- •19.4 PRISM Cloud Implementation
- •19.4.1 Cloud Resources
- •19.4.2 Cloud Service Deployment and Management
- •19.5 The PRISM Deployment
- •19.6 Summary
- •19.7 Content Note
- •References
- •20.1 Cloud Computing Reference Model
- •20.2 Cloud Economics
- •20.2.1 Economic Context
- •20.2.2 Economic Benefits
- •20.2.3 Economic Costs
- •20.2.5 The Economics of Green Clouds
- •20.3 Quality of Experience in the Cloud
- •20.4 Monetization Models in the Cloud
- •20.5 Charging in the Cloud
- •20.5.1 Existing Models of Charging
- •20.5.1.1 On-Demand IaaS Instances
- •20.5.1.2 Reserved IaaS Instances
- •20.5.1.3 PaaS Charging
- •20.5.1.4 Cloud Vendor Pricing Model
- •20.5.1.5 Interprovider Charging
- •20.6 Taxation in the Cloud
- •References
- •21.1 Introduction
- •21.2 Background
- •21.3 Experiment
- •21.3.1 Target Application: Value at Risk
- •21.3.2 Target Systems
- •21.3.2.1 Condor
- •21.3.2.2 Amazon EC2
- •21.3.2.3 Eucalyptus
- •21.3.3 Results
- •21.3.4 Job Completion
- •21.3.5 Cost
- •21.4 Conclusions and Future Work
- •References
- •Index
1 Tools and Technologies for Building Clouds |
17 |
[64]: (1) Deep access to existing enterprise services and data/content repositories;
(2) SaaS-style web-based Mashup assembly and use; (3) Assembly models that are truly end-user friendly with very little training required; and last, but certainly not least, (4) a credible management and maintenance plan for IT departments that must support a flood of public end-user built and integrated apps.”
Mashup is concerned with the API (application) level. When building Mashups, the developer is always dependent on the providers of the services. As shown in the figure, Mashup requires that the XMLHttpRequest is made to third-party domains. By compositing services and data from SOA, REST, RSS, ATOM, and other RPClike web servers, a Mashup API can conveniently bind the data with AJAX scripts to deliver a service to end-users.
Some Mashup editors have been implemented to help developers easily construct Web 2.0 and cloud-oriented applications; currently two are available, Google Mashup Editor [65] and Mozilla Ubiquity [66].
1.4.5 Web Services in Practice
All the aforementioned web services tools and technologies have been widely implemented by industry and open-source organizations. Table 1.4 also lists their main attributes in terms of when they were proposed, dependencies, transport mechanism, key technology, categories, and implementations. Understanding these features can help developers to quickly adopt the appropriate technologies and develop their clouds effectively.
1.5 Conclusions
This chapter has presented the main tools and technologies for building and operating clouds. Virtualization technology is foundational to cloud computing because it provides a safe and flexible platform using VMs, VM Monitors, Virtual Infrastructure, and Cloud Infrastructure Managers. Virtualization technology is still developing rapidly, and some of the limitations that currently exist are likely to be addressed as virtualization technology becomes more mature. We have also presented the MapReduce programming model, which is a particularly useful approach for processing huge amounts of data because the computation is close to the data.
Finally, we have reviewed a number of different web services technologies that provide an easy interface for users to configure and access cloud resources.
Cloud computing is a powerful way to provide computing resources, and the tools for creating and maintaining cloud systems and their services are becoming increasingly flexible and easy to use, providing users with easy on-demand access to massive computing power and storage that previously would only have been available to extremely well-resourced organizations.
18 |
H. Jin et al. |
Acknowledgments This work is supported by National 973 Key Basic Research Program under grant No.2007CB310900, NSFC under grants No.60673174 and No.60973037, Program for New Century Excellent Talents in University under Grant NCET-07-0334, Information Technology Foundation of MoE and Intel under grant MoE-INTEL-09-03, and National High-Tech R&D Plan of China under grant No.2006AA01A115.
References
1.APPRIO Homepage (2009) http://www.appirio.com/
2.Force.com Homepage (2009) http://www.salesforce.com/platform/
3.Amazon Web Services (2009) http://aws.amazon.com/
4.Barroso LA, Urs Hölzle U (2009) The datacenter as a computer: an introduction to the design of warehouse-scale machines. Morgan & Claypool, USA
5.ADO.NET Data Service (formally Astroia) (2009) http://msdn.microsoft.com/en-us/data/ bb931106.aspx
6.Google AppEngine (2009) http://code.google.com/appengine/
7.Amazon Elastic Cloud Computing (2009) http://aws.amazon.com/ec2/
8.Enomaly Elastic Computing (2009) http://www.enomaly.com/
9.Open Nubela Homepage (2009) http://www.opennebula.org/
10. Rightscale Homepage (2009) http://www.rightscale.com/
11. Elastra Manage ComplexITy Homepage (2009) http://www.elastra.com/
12. Dean J, Ghemawat S (2008) MapReduce: simplified data processing on large clusters. Commun ACM 51(1):107–113
13. Patterson DA (2008) Technical perspective: the data center is the computer. Commun ACM 51(1):105
14. Vmware (2009) http://www.vmware.com/virtualization/history.html
15. Goldberg RP (1974) Survey of virtual machine research. IEEE Comput Mag 7(6):34–45
16. Waldspurger CA (December 2002) Memory resource management in VMware ESX server. In: Proceedings of the 5th symposium on operating systems design and implementation (OSDI ’02), Boston, MA
17. Fraser K, Hand S, Neugebauer R, Pratt I, Warfield A, Williamson M (2004) Safe hardware access with the Xen virtual machine monitor. In: OASIS ASPLOS 2004 workshop
18. Clark C, Fraser K, Hand S, Hansen JG, Jul E, Limpach C, Pratt L, Warfield A (2005) Live migration of virtual machines. In: Proceedings of the 2nd symposium on networked systems design and implementation (NSDI ’05), Boston, MA
19. Garfinkel T, Pfaff B, Chow J, Rosenblum M, Boneh D (2003) Terra: a virtual machine-based platform for trusted computing. In: Proceedings of the 19th ACM symposium on operating systems principles (SOSP ’03), Bolton Landing (Lake George), New York
20. Bressoud TC, Schneider FB (1995) Hypervisor based fault tolerance. In: Proceedings of the fifteenth ACM symposium on operating systems principles, ACM Press, pp 1–11
21. Petrini F, Kerbyson DJ, Pakin S (2003) The case of the missing supercomputer performance: achieving optimal performance on the 8,192 processors of ASCI Q. In: Proceedings of SC ’03, Washington, DC, USA
22. Koch K (2002) How does ASCI actually complete multi-month 1000-processor milestone simulations? In: Proceedings of the conference on high speed computing
23. Foster I, Zhao Y, Raicu I, Lu S (2008) Cloud computing and grid computing 360-degree compared. In: the Proceedings of the grid computing environments workshop
24. Nanda S, Chiueh T (2005) A survey on virtualization technologies, RPE Report, February. www.ecsl.cs.sunysb.edu/tr/TR179.pdf
25. Virtual Machine (Wikipedia) (2009) http://en.wikipedia.org/wiki/Virtual_machine
1 Tools and Technologies for Building Clouds |
19 |
26. IBM white paper (2009) Seeding the Clouds: Key Infrastructure Elements for Cloud Computing. ftp://ftp.software.ibm.com/common/ssi/sa/wh/n/oiw03022usen/OIW03022USEN.PDF
27. VMware – Virtual Infrastructure Software (2009) http://www.vmware.com.
28. Xen Homepage (2009) http://www.xen.org/.
29. Kernel-based Virtual Machine (2009) http://kvm.qumranet.com.
30. Microsoft Hyper-V (2009) http://www.microsoft.com/hyper-v-server/en/us/default.aspx
31. Pratt I, Warfield A, Barham P, Neugebauer R (2003) Xen and the art of virtualization. In Proceedings of the 19th ACM symposium on operating systems principles (SOSP ’03), Bolton Landing (Lake George), New York
32. Whitaker A, Shaw M, Gribble SD (2002) Scale and performance in the Denali isolation kernel. In: Proceedings of the 5th symposium on operating systems design and implementation (OSDI’02), Boston, MA
33. MSDN Architecture Center, Mapping Applications to the Cloud (2009) http://msdn.microsoft. com/en-us/library/dd430340.aspx
34. Comparison of platform virtual machines (Wikipedia) (2009) http://en.wikipedia.org/wiki/ Comparison_of_platform_virtual_machines
35. Eucalyptus system Homepage (2009) http://www.eucalyptus.com/
36. Nimbus Homepage (2009) http://workspace.globus.org/
37. Elastic Hosts Homepage (2009) http://www.elastichosts.com/
38. McNett M, Gupta D, Vahdat A, Voelker GM (2007) Usher: an extensible framework for managing clusters of virtual machines. 21st Large installation system administration conference 39. Shi XH, Tan H, Wu S, Jin H (2008) VNIX: managing virtual machines on clusters, pp 155–
162. Japan-China joint workshop on frontier of computer science and technology
40. OGF Open Cloud Computing Interface Working Group (2009) http://www.occi-wg.org/ doku.php
41. VMan Initiative (2009) http://www.dmtf.org/initiatives/vman_initiative/
42. libvirt: The virtualization API (2009) http://libvirt.org/
43. RightScale – Testimonials (2009) http://www.rightscale.com/customers/
44. Kaavo Homepage (2009) http://www.kaavo.com/home
45. Kaavo – Testimonials (2009) http://www.kaavo.com/testimonials
46. CohesiveFT Homepage (2009) http://www.cohesiveft.com/
47. Ghemawat S, Gobioff H, Leung ST (2003) The google file system. In: the proceedings of the 19th ACM symposium on operating systems principles, Lake George, New York
48. Hadoop (2009) http://lucene.apache.org/
49. Yahoo! (2009)Yahoo! Developer Network. http://developer.yahoo.com/blogs/hadoop/2008/02/ yahoo-worlds-largest-production-hadoop.html. Accessed September 2009
50. Hadoop Credits Page (2009) http://hadoop.apache.org/core/credits.html. Accessed September
2009
51. CloudStore (Formely Kosmos File System) (2009) http://kosmosfs.sourceforge.net/
52. .NET Remoting, http://en.wikipedia.org/wiki/.NET_Remoting
53. Java RMI, http://en.wikipedia.org/wiki/Java_RMI
54. J2EE, http://en.wikipedia.org/wiki/J2EE
55. Service Oriented Architecture (Wikipedia) (2009) http://en.wikipedia.org/wiki/Serviceoriented_architecture
56.Service-architecture – Service-oriented architecture (SOA) definition (2009) http://www.service- architecture.com/web-services/articles/service-oriented_architecture_soa_definition.html
57. WSRF (2009) http://www.oasis-open.org/committees/wsrf/
58. WS-Security (2009) http://www.oasis-open.org/committees/tc_home.php?wg_abbrev=wss 59. WS-Policy (2009) http://www.w3.org/Submission/WS-Policy/
60. Goth G (2004) Critics say web services need a REST. IEEE Distribut Syst Online 5(12): 1–1 61. Vinoski S (2008) RESTful web services development checklist. IEEE Internet Comput
12(6):94–96
62. Vinoski S ((2007) REST eye for the SOA guy. IEEE Internet Comput 11(1):82–84
20 |
H. Jin et al. |
63. Mashup (web application hybrid), http://en.wikipedia.org/wiki/Mashup_(web_application_hybrid) 64. Webmashup.com blog, http://www.webmashup.com/blog/category/learn/ (accessed 1 October
2009)
65. Google Mashup Editor (2009) http://en.wikipedia.org/wiki/Google_Mashup_Editor 66. Mozilla Ubiquity (2009) http://ubiquity.mozilla.com/