Preface
Contents
Abbreviations
List of Figures
List of Tables
Chapter 1: Introduction to Multilayered Cloud Computing
1.1 Introduction
1.2 Characteristics of Cloud [13]
1.3 Type of Cloud and Its Services
1.4 Issues in Cloud Computing
1.4.1 Resource Allocation
1.4.2 Load Balancing
1.4.3 Migration
1.4.4 Power-Efficient Resource Allocation and Load-Balancing Algorithms
1.4.5 Cost-Efficient Resource Allocation and Load-Balancing Algorithms
1.4.6 Fault-Tolerant Algorithms
1.4.7 Behavior-Based Algorithms
1.4.8 Trust Management
1.5 Multilayered Cloud Architecture
1.6 Role of Trust in Cloud and Its Various Services
1.7 Summary
References
Chapter 2: Trust and Reliability Management in the Cloud
2.1 Introduction
2.1.1 What Is Trust?
2.2 Security Challenges
2.3 Role of Trust in Multilayered Cloud
2.3.1 Evaluation of Trust
2.3.2 Trust Management and Performance Improvement
2.4 Existing Trust-Based Solutions in Cloud
2.4.1 Cloud Service Registry and Discovery Architecture
2.5 Comparison with Various Reported Literature
2.5.1 Parameters Affecting Trust Models in Multi-Cloud Architecture
2.6 Summary
References
Chapter 3: Trust Evaluation and Task Scheduling in Cloud Infrastructure
3.1 Introduction
3.2 Trust Evaluation in Multilayered Cloud
3.2.1 Evaluation of Trust
3.2.2 Trust Management and Performance Improvement
3.3 Trust-Aware Task-Scheduling Techniques in Multilayered Cloud
3.4 Trust and Reliability-Based Algorithm
3.4.1 Existing Trust-Aware Task Scheduling
3.5 Proposed Trust Management Technique for Task Scheduling
3.5.1 Motivation
3.5.2 Algorithm and Layered Architecture
Trust- and Deadline-Aware Scheduling Algorithm for Cloud Infrastructure Using Ant Colony Optimization
Proposed Algorithm
Experiment and Results
Trust-Based Genetic Algorithm for Cloud Infrastructure
3.6 Experiment and Results
3.6.1 Trust-Aware Big-Bang-Big Crunch Algorithm for Task Scheduling in Cloud Infrastructure
3.7 Experiment and Results
3.8 Evaluation of Proposed Algorithm
3.9 Summary
References
Further Reading
Chapter 4: Trust Modeling in Cloud
4.1 Introduction
4.2 Characteristics of Cloud [2, 3]
4.3 Issues in Cloud Computing
4.3.1 Security Issues
4.3.2 Privacy Issues
4.3.3 Trust Issues
4.4 Security, Privacy, and Trust Issues in SaaS and PaaS
4.4.1 Approaches to Maintain Security, Privacy, and Trust Issues [6, 18]
4.5 Trust Related Problem in SaaS Cloud
4.6 Establishing Trust Model in SaaS
4.7 Trust Based SaaS Scenarios
4.7.1 Scenario 1: SOC
4.7.2 Scenario 2: Data Accountability and Auditability
4.8 Summary
References
Chapter 5: Trust Modeling in Cloud Workflow Scheduling
5.1 Introduction
5.1.1 Heuristic Workflow Scheduling Algorithms
5.1.2 Metaheuristic/Nature-Inspired Workflow Scheduling Algorithms
5.2 Trust Model
5.2.1 Type of Trust Models
5.2.2 Parameters Affecting Trust
5.3 Trust Models for Workflow Scheduling
5.4 Proposed Trust-Aware Workflow Scheduling in Cloud
5.4.1 Proposed Trust-Based Max-Min Algorithm
5.4.2 Proposed Trust-Based Min-Min Algorithm
5.4.3 Experimental Setup
5.4.4 Experiment and Result Analysis
5.5 Summary
References
Chapter 6: Fault-Aware Task Scheduling for High Reliability
6.1 Introduction
6.2 Fault Tolerance in Cloud
6.3 Taxonomy of Fault-Tolerant Task Scheduling Algorithms
6.3.1 Approach 1: Fault- and QoS-Based Genetic Algorithm for Task Allocation in Cloud Infrastructure [10]
Proposed Algorithm
Experiment and Results
6.3.2 Approach 2: Fault-Tolerant Big-Bang-Big Crunch for Task Allocation in Cloud Infrastructure [13]
Proposed Algorithm
Experiment and Results
6.3.3 Approach 3: Load- and Fault-Aware Honey Bee Scheduling Algorithm for Cloud Infrastructure [14]
Proposed Algorithm
Experiment and Result
6.3.4 Approach 4: Power and Fault Awareness of Reliable Resource Allocation for Cloud Infrastructure [23]
Proposed Algorithm
Experimental and Results
6.3.5 Comparative Analysis of Learning-Based Algorithms
6.4 Summary
References
Chapter 7: Fault Model for Workflow Scheduling in Cloud
7.1 Introduction
7.1.1 Fault in Workflow
7.2 Taxonomy of Fault-Tolerant Scheduling Algorithms
7.3 Proposed Model
7.3.1 Approach 1: Fault-Aware Ant Colony Optimization for Workflow Scheduling in Cloud
Proposed Algorithm
Experiment and Results
7.3.2 Approach 2: Fault- and Cost-Aware Ant Colony Optimization
Methodology
Experimental Results
7.4 Comparison of Results
7.5 Performance Evaluation
7.6 Summary
References
Chapter 8: Tools for Fault and Reliability in Multilayered Cloud
8.1 Tools for Workflow Management
8.1.1 Workflows [1]
8.1.2 CloudSim 3.0 [2]
8.1.3 SimpleWorkflow
8.1.4 mDAG
8.2 Tools for Fault Simulation in Cloud IaaS
8.2.1 FTCloudSim [3]
8.2.2 CloudSim Plus [4]
8.2.3 FIM-SIM [5]
8.2.4 Cloud Deployment Tools
8.3 Scalability Simulation Tool
8.3.1 ElasticSim [24]
8.3.2 CloudSim 5.0 [2, 25]
8.3.3 DynamicCloudSim [26]
8.3.4 CloudSim Plus [4]
8.4 Cloud Model Simulation Tools
8.4.1 CloudSim [2]
8.4.2 CloudAnalyst [27]
8.4.3 GreenCloud [28]
8.4.4 iCanCloud [29]
8.4.5 EMUSIM [30]
8.4.6 CloudReports [31]
8.4.7 GroudSim [32]
8.4.8 DCSim (Data Center Simulation) [33]
8.4.9 CloudSimEx [34]
8.4.10 Cloud2Sim [35]
8.4.11 RealCloudSim [36]
8.4.12 CloudAuction [37]
8.4.13 FederatedCloudSim [38]
8.5 Raw Data for Simulation of Fault in the Cloud
8.5.1 Parallel Workload Archive [39]
8.5.2 Google Cluster Data
8.5.3 Alibaba Cluster Data
8.5.4 The QWS Dataset
8.6 Summary
References
Chapter 9: Open Issues and Research Problems in Multilayered Cloud
9.1 Introduction
9.2 Privacy Issues in Cloud Computing
9.3 Trust Issues in Cloud Computing
9.4 Open Issues in Fog Computing
9.5 Open Issues in the Internet of Things (IoT)
9.6 Summary
References
Index