
- •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

Chapter 20
Cloud Economics: Principles, Costs,
and Benefits
Asoke K. Talukder, Lawrence Zimmerman, and Prahalad H.A
Abstract Cloud computing is an important next step in the trend toward inexpensive and universal access to information and sophisticated computing resources that help close the digital divide between the computer haves and have-nots. In cloud computing, the end-users can access fully functional software and services online at little or no cost using inexpensive computers or mobile communication devices that connect them via the Internet. Innovative service providers no longer need to own and maintain development or production infrastructures and can automatically scale their production operations to meet growing demand much more easily and economically than possible with internal data centers, traditional hosting, or managed services arrangements. The cloud’s inherent ability to dynamically scale up or scale down the infrastructure commitment as demand changes on a pay-as-you-go basis has a positive impact on the service provider’s overhead costs, energy costs, and in reducing its carbon footprint.
Cloud economics as presented in this chapter refers to the economic forces, business drivers, and structural issues affecting the broad costs and benefits of adopting the cloud technologies or the creation of private or public utility clouds. Here, cloud economics also deal with the economy inside the cloud, which includes monetization, charging, billing, and taxation of products and services inside the cloud.
20.1 Cloud Computing Reference Model
The cloud can be divided into three major verticals, namely, the cloud user, the cloud vendor, and the original cloud provider (OCP) as shown in Fig. 20.1. The cloud vendor is an organization that has a local tax registration and offers the cloud services to the cloud user with guaranteed quality of experience (QoE) and quality of service (QoS)
A.K. Talukder (*)
Geschickten Solutions, Bangalore, India e-mail: asoke.talukder@gmail.com
N. Antonopoulos and L. Gillam (eds.), Cloud Computing: Principles, |
343 |
Systems and Applications, Computer Communications and Networks,
DOI 10.1007/978-1-84996-241-4_20, © Springer-Verlag London Limited 2010

344 |
A.K. Talukder et al. |
within the framework of a service level agreement (SLA). A cloud vendor can be a compute, storage and application brokerage and clearing house that provides prenegotiated access to the cloud services such as infrastructure as a service (IaaS) provider, platform as a service (PaaS) provider, and software as a service (SaaS) provider [1]. The IaaS service provider offers the physical computing hardware that includes the processing power through a set of central processing units (CPUs) in a cluster. IaaS will also provide the online memory (Random Access Memory – RAM) and the disk storage. The PaaS provider is responsible for supplying and managing all the middleware platforms necessary to enable the software to run over the cloud. Finally, the SaaS provider will offer the software applications that will be used by the end-user.
The cloud vendor offers the QoE and the QoS that the end-user requires; the cloud vendor will provide the data security and meet the regulatory and legal requirements as required by the user or the regulators. The cloud vendor ensures that SaaS, PaaS, and IaaS are available to the end-user as services that are elastic and can scale up or scale down on demand. The cloud vendor also guarantees that the cloud service is fault-tolerant and is available on a continuous basis with proper security that includes confidentiality, integrity, availability, authentication, authorization, accounting, and anonymity (CI5A) [2]. The cloud vendor will charge the end-user for the consumed cloud resources based on the QoE.
At one time, energy companies used to manufacture power transmit it from generating stations to the distribution center, and finally deliver it to a household for a fee. The same was also true with telecommunications vendors who used to own the entire infrastructure starting from customer premises equipment to the transmission line. However, today many telecom and energy resellers are virtual operators who do not own any infrastructure. They use energy and telecom infrastructures from different providers to offer better QoS, cheaper tariffs, or value-added services.
|
|
Q |
M |
|
S |
o |
|
|
I |
||
|
E |
||
|
E |
D |
|
User/ |
|
||
C |
|
D |
|
Customer/ |
U |
& |
L |
Device |
R |
E |
|
|
I |
|
W |
|
T |
Q |
A |
|
Y |
R |
|
|
o |
||
|
|
E |
|
|
|
S |
|
|
|
|
Presentation Modality |
|
Presentation Platform |
|
|
|
API |
|
|
|
Application |
|
Software as |
||
|
a Service |
|||
Data |
Metadata |
Content |
|
|
Integration & Middleware |
Integration & Middleware |
Platform as |
||
|
|
|
|
a Service |
API |
|
|
API |
|
Connectivity & deliveryvery |
Connectivity & deliveryvery |
|
|
|
Infrastructure |
Facilities |
Facilities |
as a Service |
Hardware |
Hardware |
Facilities |
Facilities |
Cloud User Cloud Vendor |
Original Cloud Provider |
Fig. 20.1 The cloud reference model