New Frontiers in Cloud Computing and Internet of Things

Preface
The Book Organisation
Cloud Computing
Internet of Things (IoT)
Acknowledgements
Contents
Part I Cloud Computing
1 Cloud Computing and Internet of Things: Recent Trends and Directions
Contents
1.1 Introduction
1.1.1 Cloud Computing
1.1.2 Internet of Things (IoT)
1.2 Key Cloud Technologies and Services
1.2.1 Infrastructure as a Service (IaaS)
1.2.2 Container as a Service (CaaS)
1.2.3 Platform as a Service (PaaS)
1.2.4 Function as a Service (FaaS)
1.2.5 Software as a Service (SaaS)
1.3 Key IoT Technologies and Applications
1.3.1 Things
1.3.2 Communication Protocols
1.3.2.1 IoT Data Protocols
1.3.2.2 IoT Network Protocols
1.3.3 IoT Frameworks
1.3.3.1 Proprietary-Based
1.3.3.2 Open Source
1.3.4 Deployment Models
1.3.4.1 Cloud-Centric IoT
1.3.4.2 Edge/Fog-Centric IoT
1.3.5 Applications
1.4 Modeling and Simulation Toolkits
1.5 Open Challenges
1.6 Summary
References
2 Recent Advances in Energy-Efficient Resource Management Techniques in Cloud Computing Environments
Contents
2.1 Introduction
2.1.1 Motivation and Contribution
2.2 Related Work
2.3 Proposed Taxonomy for Energy-Aware Resource Management Solutions in Cloud Environments
2.3.1 Goals
2.3.2 Workload
2.3.3 Resources
2.3.4 Dynamism
2.3.4.1 Static Power Management (SPM)
2.3.4.2 Dynamic Power Management (DPM)
2.4 Virtualization Level
2.4.1 Migration
2.4.1.1 VM Migration Type
2.4.1.2 Container Migration Type
2.4.1.3 Migration Cost
2.4.2 Consolidation
2.4.2.1 Consolidation Level
2.4.2.2 Consolidation Subproblems
2.5 Comparing the State of the Art
2.6 Future Scope and Conclusion
2.6.1 Conclusion
References
3 Multi-objective Dynamic Virtual Machine Consolidation Algorithm for Cloud Data Centers with Highly Energy Proportional Servers and Heterogeneous Workload
Contents
3.1 Introduction
3.2 Related Work
3.3 Modelling Stochastic VM Release Time, Notations Used and Important Concepts
3.3.1 Modelling Stochastic VM Release Time, PM Release Time and Notations Used
3.3.2 Modelling Resource Utilization and Constraints
3.3.3 Modelling Energy Consumption
3.3.4 Objective Functions
3.4 Proposed Solution
3.4.1 Two Phases of SRTDVMC Algorithm
3.4.1.1 The First Phase O-UPMs
3.4.1.2 The Second Phase U-UPMs
3.4.2 Characteristics of Proposed Algorithm
3.5 Performance Evaluation
3.5.1 Experimental Setup
3.5.2 Performance Metrics and Workload Data
3.5.2.1 Performance Metrics
3.5.2.2 Workload Data
3.6 Simulation Results Analysis
3.6.1 Energy Consumption
3.6.1.1 Normality Testing
3.6.1.2 Parametric Hypothesis Testing and Test Error
3.6.2 VM Migration
3.6.2.1 Normality Testing
3.6.2.2 Parametric Hypothesis Testing and Test Error
3.7 Observations
3.8 Conclusions and Future Work
3.8.1 Conclusions
3.8.2 Future Work
References
4 Energy-Efficient Resource Management of Virtual Machine in Cloud Infrastructure
Contents
4.1 Introduction
4.2 Background
4.3 Proposed Work
4.3.1 Design of Cloud Environment
4.3.2 Selection of Workload
4.3.3 Allocation Policy
4.3.3.1 Genetic Algorithm
4.3.3.2 Shuffled Frog Leaping Algorithm
4.3.4 Framework Monitor
4.3.5 Migration of Virtual Instances
4.3.5.1 High Loaded Host Detection
4.3.5.2 Low Loaded Host Detection
4.3.6 VM Selection Policy
4.3.6.1 Minimum Time on Migration (MTM)
4.4 Result and Analysis
4.4.1 Experimental Results
4.4.2 Analysis of Complexity of Time
4.5 Conclusion and Future Work
References
5 Dynamic Resource-Efficient Scheduling in Data Stream Management Systems Deployed on Computing Clouds
Contents
5.1 Introduction
5.2 Background
5.3 Dynamic Resource-Efficient Scheduling
5.3.1 Problem Formulation
5.3.2 Heuristic-Based Scheduling Algorithm
5.3.3 Complexity Analysis
5.4 Implementation of D-Storm Prototype
5.5 Performance Evaluation
5.5.1 Experiment Setup
5.5.1.1 Test Applications
5.5.1.2 Parameter Selection and Evaluation Methodology
5.5.2 Evaluation of Applicability
5.5.3 Evaluation of Cost Efficiency
5.5.4 Evaluation of Scheduling Overhead
5.6 Related Work
5.7 Conclusions and Future Work
References
6 Serverless Platforms on the Edge: A Performance Analysis
Contents
6.1 Introduction
6.2 Background
6.2.1 Motivation
6.2.2 History of Serverless
6.2.3 Serverless at the Edge
6.3 Related Works
6.3.1 AWS Lambda
6.3.2 AWS Greengrass
6.3.3 Azure Functions
6.3.4 Apache OpenWhisk
6.3.5 OpenFaaS
6.4 Performance Evaluation
6.4.1 Experimental Setup
6.4.1.1 Testbed Setup
6.4.1.2 Test Functions
6.4.2 Results
6.4.2.1 CPU-Intensive Functions
6.4.2.2 Memory-Intensive Functions
6.4.2.3 Disk-Intensive Functions
6.5 Discussions
6.6 Conclusions and Future Work
Bibliography
7 ITL: An Isolation-Tree-Based Learning of Features for Anomaly Detection in Networked Systems
Contents
7.1 Introduction
7.2 Related Work
7.3 Model Assumptions and an Overview on Isolation-Based Anomaly Detection
7.4 ITL Approach
7.4.1 Feature Refinement Process
7.5 Performance Evaluation
7.5.1 Experimental Settings
7.5.2 Experiment Results
7.5.2.1 ITL with Bagging of the Scores
7.5.2.2 ITL with Reduced Features
7.5.2.3 Time Complexity and Runtime Analysis
7.5.3 Strength and Limitations of ITL Approach
7.6 Conclusions and Future Work
References
8 Digital Twin of a Cloud Data Centre: An OpenStack Cluster Visualisation
Contents
8.1 Introduction
8.2 Background
8.2.1 A Taxonomy of Digital Twin Characteristics
8.2.1.1 Digital Twin Usage
8.2.1.2 Period of Production
8.2.1.3 Connection Between Physical Twin and Digital Twin
8.2.1.4 Building Blocks of a Digital Twin
8.3 Digital Twin of a Cloud Data Centre Instance System
8.3.1 Unity Model
8.3.1.1 Main Components
8.3.1.2 Digital Twin Interactive Features
8.3.2 API Integration
8.4 Qualitative Study
8.5 Evaluation and Results
8.6 Discussion and Future Directions
8.7 Conclusions
References
Part II Internet of Things
9 Industrial IoT Technologies and Protocols
Contents
9.1 Introduction
9.1.1 What Is IoT?
9.1.2 The Paths for Data Transmission Through the Connectivity and Networks
9.1.3 Baseline Technologies
9.1.4 Connectivity Terminologies
9.1.4.1 Connectivity Layers
9.2 Network Topology
9.3 Addressing Manners
9.4 Sensors and Transducers
9.4.1 Types of Sensors
9.5 Components of IoT
9.5.1 Communication Protocols
9.5.2 IEEE 802.15.4
9.5.3 Zigbee
9.5.4 Wireless HART
9.5.5 NFC Communication Protocol
9.5.6 Bluetooth Communication Protocol
9.5.7 Bluetooth Piconets
9.5.8 Z-Wave
9.5.9 ISA 100.11A
9.6 Conclusion
References
10 IoT for Sustainability
Contents
10.1 Global Trends
10.1.1 Climate Change
10.1.2 Urbanisation
10.1.3 Linear Business Models
10.1.4 Technology and Automation
10.1.5 Summary
10.2 Sustainability
10.2.1 UN Sustainable Development Goals
10.2.2 Perspectives on Sustainability
10.2.2.1 Developing Versus Developed Countries
10.2.2.2 Urban Versus Rural
10.2.2.3 Local Versus Global
10.2.2.4 Internal Versus External Focus
10.2.3 Computational Sustainability
10.3 The IoT Fit
10.3.1 Architecture
10.3.2 Fog Computing
10.3.3 IoT and Sustainability
10.3.4 Smart Cities
10.4 Taking Stock
10.4.1 Selective Focus
10.4.2 Top-Down Solutions
10.4.3 Digital Colonialism
10.5 Cellular Architectures
10.5.1 Resilience
10.5.2 Energy Distribution
10.5.3 Local Clouds
10.5.4 Smart Villages
10.6 Current and Future Challenges
10.7 Conclusion
References
11 Applications of IoT and Cloud Computing: A COVID-19 Disaster Perspective
Contents
11.1 Introduction
11.2 Video Conferencing
11.3 E-Gaming and Video Streaming
11.4 Future Opportunities
11.5 Application of IoT in Transportation
11.5.1 Logistics
11.5.2 Innovations
11.5.3 Applications
11.5.3.1 Inventory Tracking and Warehousing [6]
11.6 Fleet Management [7, 8]
11.7 Drone-Based Delivery (DBD) [10]
11.8 Autonomous Vehicles [12]
11.9 Future Opportunities
11.10 Manufacturing Industry During COVID-19
11.11 IoT-Enabled Automation for Remote Manufacturing and Businesses
11.12 Monitoring Using IoT
11.12.1 Vision-Based Control Systems
11.12.2 KC 901 Smart Helmet
11.12.3 Post-COVID-19 Opportunities
11.13 Applications of IoT and Cloud Computing in Healthcare
11.13.1 HealthCare
11.13.2 New Innovations
11.13.3 Applications
11.13.3.1 Remote Healthcare
11.13.3.2 Robotic Assistantship
11.14 Post-COVID-19 Opportunities
11.15 Applications of IoT and Cloud Computing in Agriculture
11.15.1 Agriculture Monitoring
11.16 Summary
11.17 Conclusion
References
12 Analytics of IoT-Based System for Monitoring Students' Progress in Educational Environment
Contents
12.1 Introduction
12.2 Review of Related Work
12.2.1 Big Data
12.2.2 The Internet of Things
12.2.3 Cloud Computing
12.2.4 RFID Sensing Technology
12.2.5 Applications of RFID Technology
12.2.6 Internet of Things and Education
12.3 Methodology
12.4 Use Case of the Proposed Framework
12.5 Conclusion and Future Research Directions
References
13 Power System Protection on Smart Grid Monitoring Faults in the Distribution Network via IoT
Contents
13.1 Introduction
13.2 Backgrounds and Literature Survey
13.2.1 Internet of Things (IoT): Communication Technology
13.2.2 Internet of Things (IoT): Machine: Machine Communication Technology
13.2.3 Protection Relay
13.2.4 Communication of IoT with Smart Grid
13.2.5 Review of the Past Research Work
13.3 Proposed Model
13.3.1 Components of the Single Line Diagram of Test Distribution Network
13.3.2 Design of the GSM Module to Be Integrated into the Tested Distribution Network
13.3.3 Simulation of Faults
13.3.3.1 Three-Phase Fault
13.3.3.2 Fault Currents Result
13.3.3.3 Relay Tripping Time
13.4 Result and Discussion
13.5 Recommendation
13.6 Conclusion
References
14 Medical Data Analysis for IoT-Based Datasets in the Cloud Using Naïve Bayes Classifier for Prediction of Heart Disease
Contents
14.1 Introduction
14.2 Background and Literature Review
14.3 Materials and Methods
14.3.1 Data Gathering
14.3.2 Data Sample
14.3.3 Data Preprocessing
14.3.4 Proposed System
14.4 Findings and Discussion
14.4.1 Weka Software Environment
14.4.2 Heart Disease Dataset Analysis
14.4.3 Attribute Value Distribution for All Attributes
14.4.4 K == 10-Fold Cross Validation Evaluation Technique
14.4.5 Detailed Result of Final Analysis (11th Run)
14.4.6 Performance Evaluation
14.4.7 Discussion
14.5 Conclusion and Future Works
References
15 The Internet of Things in Healthcare: Benefits, Use Cases, and Major Evolutions
Contents
15.1 Introduction
15.2 Related Work
15.3 IoT: Transforming Healthcare Industry
15.3.1 Delivering Healthcare Solutions
15.3.1.1 IoT for Patients
15.3.1.2 IoT for Doctors
15.3.1.3 IoT for Hospitals
15.3.1.4 IoT for Health Insurance Organizations
15.3.2 Salient Steps for Transforming the Healthcare Industry
15.4 Promising Use Cases of IoT in Healthcare
15.4.1 Reachability for Remote Patient Care
15.4.2 Emergency Care for Patients
15.4.3 Healthcare Management
15.4.4 Augmenting Surgeries
15.4.5 Risk-Based Hardware Management
15.4.6 Drugs Management
15.4.7 Wearables
15.5 State of IoT in Healthcare
15.6 Benefits of IoT in Healthcare
15.6.1 Cost-Effective
15.6.2 Quality-of-Treatment-Service
15.6.3 Efficient-Diagnosis-System
15.6.4 Action-Based Treatment
15.6.5 Medical Resource Management
15.6.6 Error Reduction
15.7 Challengers of Healthcare IoT Deployments
15.7.1 Reliable Connectivity
15.7.2 Cybersecurity
15.7.3 Scalable Platforms
15.7.4 Cost
15.8 Conclusion
References
Index