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Model-Driven Development and Operation of Multi-Cloud Applications : The MODAClouds Approach.

Bibliographic Details
Main Author: Di Nitto, Elisabetta.
Other Authors: Matthews, Peter., Petcu, Dana., Solberg, Arnor.
Format: eBook
Language:English
Published: Cham : Springer International Publishing AG, 2017.
Edition:1st ed.
Series:SpringerBriefs in Applied Sciences and Technology Series
Subjects:
Electronic books.
Online Access:Click to View
Table of Contents:
  • Intro
  • Preface
  • Contents
  • 1 Introduction
  • 1.1 Context
  • 1.2 Motivation
  • 1.3 Related Work
  • 1.4 The MODAClouds Approach
  • 1.5 The MODAClouds Toolbox
  • 1.6 Book Objectives
  • References
  • 2 Cloud Service Offer Selection
  • 2.1 Introduction: Selecting Services for Agile Application Development
  • 2.2 Decision Support System for Cloud Service Selection
  • 2.3 Cloud Service Description Standardization
  • 2.4 Data Gathering in Multi-Cloud Environments
  • 2.5 Coping with Complexity in SaaS
  • 2.6 Decision Support Tools for Cloud Service Selection
  • 2.7 Technical Challenges and Implementation
  • 2.8 Conclusion: Evolution of Cloud Services, Decision Support and Future Work
  • Reference
  • 3 The MODAClouds Model-Driven Development
  • 3.1 Introduction
  • 3.2 The Design-Time Development Process
  • 3.3 Overall Language Architecture
  • 3.4 MODACloudML Sub Models
  • 3.4.1 CCIM Models
  • 3.4.2 Example
  • 3.4.3 CPIM and CPSM Models
  • 3.4.4 Example
  • 3.5 Related Work
  • 3.6 Conclusion
  • References
  • 4 QoS Assessment and SLA Management
  • 4.1 Introduction
  • 4.2 Case Study: Meeting in the Cloud (MiC)
  • 4.3 QoS Assessment and Optimisation
  • 4.3.1 Assessment
  • 4.3.2 Optimisation
  • 4.3.3 LINE
  • 4.4 SLA Management
  • References
  • 5 Monitoring in a Multi-cloud Environment
  • 5.1 Introduction
  • 5.2 Tower 4Clouds Architecture
  • 5.3 Application Configuration Model
  • 5.4 Monitoring Rules
  • 5.5 Conclusion
  • References
  • 6 Load Balancing for Multi-cloud
  • 6.1 Introduction
  • 6.2 Load Balancing Controller
  • 6.3 Load Balancing Reasoner
  • 6.4 Multi-cloud Load Balancing
  • 6.4.1 Usage Scenario of Multi-cloud Load Balancing
  • 6.5 Load Balancing and Failure Management
  • 6.6 Conclusion
  • References
  • 7 Fault-Tolerant Off-line Data Migration: The Hegira4Clouds Approach
  • 7.1 Introduction
  • 7.2 Hegira4Clouds Intermediate Meta-Model.
  • 7.3 Architecture and Fault Tolerance Features
  • 7.3.1 Virtual Data Partitioning
  • 7.3.2 Recovering from Faults
  • 7.4 Evaluation: Migrating Tweets
  • 7.5 Discussion and Conclusion
  • References
  • 8 Deployment of Cloud Supporting Services
  • 8.1 Introduction
  • 8.2 MODAClouds Execution Platform
  • 8.2.1 mOS
  • 8.2.2 Platform Sub-systems
  • 8.3 Supporting Services
  • 8.3.1 Object Store
  • 8.3.2 Artifact Repository
  • 8.3.3 Load Balancer Controller
  • 8.3.4 Batch Engine
  • 8.4 Conclusions
  • References
  • 9 Models@Runtime for Continuous Design and Deployment
  • 9.1 Introduction
  • 9.2 The Models@Runtime Approach
  • 9.3 The MODAClouds Models@Runtime Engine
  • 9.3.1 The Comparison Engine
  • 9.3.2 Adaptation Commands
  • 9.3.3 State Tracking
  • 9.3.4 Interaction with the Models@Runtime Engine
  • 9.4 Related Work
  • 9.5 Conclusion
  • References
  • 10 Closing the Loop Between Ops and Dev
  • 10.1 Introduction
  • 10.2 FG Architecture
  • 10.2.1 FG Analyzer
  • 10.2.2 FG Actuator
  • 10.2.3 FG Reporter
  • 10.3 Workflow
  • 10.4 Estimation Techniques for FG Analysis
  • 10.4.1 A Bayesian Approach Based on Queue-Lengths
  • 10.4.2 A Maximum-Likelihood Approach Based on Queue-Lengths and Response Times
  • 10.5 Conclusion
  • References
  • 11 Cloud Patterns
  • 11.1 Introduction
  • 11.2 Motivational Guidance
  • 11.3 MODAClouds-Specific Patterns
  • 11.4 Conclusions
  • References
  • 12 Modelio Project Management Server Constellation
  • 12.1 Introduction
  • 12.2 Proposed Architecture
  • 12.3 Use of MODAClouds Design and Runtime Components
  • 12.3.1 Modelling with Creator 4Clouds
  • 12.3.2 Multi-cloud Deployment with CloudML 4Clouds
  • 12.3.3 Cost and Performance Analysis with SPACE 4Clouds
  • 12.3.4 Multi-cloud Monitoring and Management with Energizer 4Clouds
  • 12.4 Conclusion
  • References
  • 13 BPM in the Cloud: The BOC Case
  • 13.1 Introduction.
  • 13.2 Context and Motivation
  • 13.3 Application Scenario
  • 13.3.1 Cloud Provider Selection
  • 13.3.2 Application Deployment to Multiple Clouds
  • 13.3.3 Cloud Application Monitoring
  • 13.3.4 Cloud to Cloud Migration
  • 13.4 Conclusion and General Recommendations
  • References
  • 14 Healthcare Application
  • 14.1 Introduction
  • 14.2 EHealth Cloud Solution: Why to Deploy It in a Multi-Cloud Environment?
  • 14.3 Risks and Problems
  • 14.4 EHealth and MODAClouds: The Story
  • 14.5 Conclusions
  • References
  • 15 Operation Control Interfaces
  • 15.1 Introduction
  • 15.2 Language for Triggers Description
  • 15.3 Architecture of the Trigger Support
  • 15.4 Usage of Triggers to Enable Load Balancing
  • 15.5 Related Work
  • 15.6 Conclusions
  • References
  • 16 Conclusion and Future Research
  • 16.1 Summary
  • 16.2 Outlook and Further Research.

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