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

• Superior document: SpringerBriefs in Applied Sciences and Technology Series
• Author: Di Nitto, Elisabetta.
• TeilnehmendeR: Matthews, Peter.; Petcu, Dana.; Solberg, Arnor.
• Place / Publishing House: Cham : : Springer International Publishing AG,, 2017.; Ã2017.
• Year of Publication: 2017
• Edition: 1st ed.
• Language: English
• Series: SpringerBriefs in Applied Sciences and Technology Series
• Physical Description: 1 online resource (154 pages)

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.