- •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
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K.W.S. Morrison |
integrity. Logs, in contrast, have immediate relevancy for diagnostic purposes, but less long-term value for forensics. As a result, logs commonly rotate automatically over old entries to keep the collection size within reasonable bounds.
Persistence of logs and audits in cloud providers is problematic. Audits (and optionally logs) must stream to long-term resilient storage instead of local disks that will be lost on instance termination. Syslog is one accepted mechanism to do this. Audits, however, should also be cryptographically secure to prevent disclosure of sensitive message contents (such as security credentials), and to guard against alteration. This can be computationally expensive to apply at run time.
Audit volumes can be very large. Data transfer costs between cloud providers on-premise faculties can be very high [1], making streaming or export of audit and log data to existing tools impractical.
Metrics collection may also produce very large data volumes. It is often necessary to record historical transaction rates for purposes of future load planning, so most SOA PEPs maintain sliding counters describing each service under their management. Depending on the time granularity of the bin, these data structures can become extremely large. Regular transfer to on-premise storage can incur considerable cost. Leveraging inexpensive local cloud storage can offset this, as evaluation of this data generally involves a rollup inside a reporting engine that can reside in the cloud.
Other existing SOA PEP alerting mechanisms may also be infeasible in the cloud. Policy-driven alerts that use SNMP to communicate with on-premise management infrastructure may be impractical because of security risks and latency. SMTP-based altering, common in on-premise SOA, may not be feasible to implement in the cloud. Cloud providers do not want their platforms to become a launching pad for spam traffic, so may block outgoing SMTP traffic. Furthermore, there are anecdotal reports of organizations blacklisting mail from Amazon AWS IP ranges because of the threat of spam [25].
A final issue is event correlation between infrastructure elements during forensic investigation. In traditional on-premise SOA, logs from routers, load balancers, and conventional firewalls provide extremely valuable data to operators investigating issues, such as an attack or transaction failure. These data are not available to customers in the cloud.
18.4.14 Repositories
One of the challenges of virtualized cloud environments is the ephemeral nature of the operating environment. Centralized policy and configuration repositories provide an important service in cloud environments to manage this. They function as the system of record – that is, the central authoritative source for policy and configuration that can be pushed to PEP enforcement points. Repositories must leverage long-term, scalable storage in cloud environments to mitigate potential loss of data on instance termination.
18 Technologies for Enforcement and Distribution of Policy in Cloud Architectures |
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Commercial SOA registry/repository offerings, such as those from SoftwareAG, HP, and IBM, take on management of all the metadata associated with services. These incorporate workflow around asset creation and authorization, environment migration, and deployment of policy and service into production. At present, these are not cloud-centric. Turnkey cloud management and security solutions, such as RightScale and Symplified, implicitly have some of these capabilities in their offerings, but these are not general cloud registry/repositories. The generalized cloud policy registry/ repository will become an important infrastructure component for cloud-based PEPs, but at present, there are no commercially successful implementations of this.
18.4.15 Provisioning and Distribution
Policy naturally assimilates dependencies on local information that may change as the policy moves between environments. Consider a migration from development, to QA, and finally into production environments: the IP addresses change, as do dependencies on external systems such as PDPs, representations of identity, etc.
Elastic computing exacerbates the dependency problem. Policy content may change in response to variation in traffic volume. Some of these changes are deterministic and thus solvable using simple mappings applied to policy documents. At present, there is no comprehensive and standardized solution to this challenge.
18.4.16 Policy Synchronization and Views
Synchronization of policy between PEPs in the on-premise DMZ and PEPs deployed in the cloud is an open issue. The existing protocols address some simple aspects of security. SSL/TLS, for example, incorporates a negotiation mechanism that converges on a cipher suite common to both parties. A similar approach is required for other aspects of policy.
WS-Security Policy (Nadalin et al. 2007) provides a means for a service provider to declare a means to secure a transaction using either SSL or WS-S messagebased security. Its scope includes confidentiality, integrity, and security tokens.
This approach provided the much-needed declarative policy around security, but much work remains. There is a need for a standardized approach to negotiate a reciprocal policy contract (like SSL does), as well as declaration of traditionally out-of-band parameters of policy such as transport compression. In the absence of this, synchronization of policy remains largely a manual operation.
The determination of appropriate policy views for a client, based on factors such as identity and entitlements, is an open area of research. All policies contain elements not intended for client consumption, such as authorization rules or internal routing. Accurate and secure resolution of suitable externally facing views of policy is an unresolved problem in need of further investigation.
