Cloud Computing and Virtualization

Inbunden, Engelska, 2018

Av Dac-Nhuong Le, Raghvendra Kumar, Gia Nhu Nguyen, Jyotir Moy Chatterjee

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The purpose of this book is first to study cloud computing concepts, security concern in clouds and data centers, live migration and its importance for cloud computing, the role of firewalls in domains with particular focus on virtual machine (VM) migration and its security concerns. The book then tackles design, implementation of the frameworks and prepares test-beds for testing and evaluating VM migration procedures as well as firewall rule migration. The book demonstrates how cloud computing can produce an effective way of network management, especially from a security perspective.

Produktinformation

Utgivningsdatum2018-03-23
Mått10 x 10 x 10 mm
Vikt454 g
FormatInbunden
SpråkEngelska
Antal sidor240
FörlagJohn Wiley & Sons Inc
ISBN9781119487906

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Dac-Nhuong Le obtained his PhD in computer science from Vietnam National University, Vietnam in 2015. He is Deputy-Head of Faculty of Information Technology, Haiphong University, Vietnam. His area of research includes: evaluation computing and approximate algorithms, network communication, security and vulnerability, network performance analysis and simulation, cloud computing, IoT and image processing in biomedical. He has authored 4 computer science books and has multiple research articles in international journals. Raghvendra Kumar completed his PhD in the Faculty of Engineering and Technology, Jodhpur National University, India. He has authored several research papers in Scopus indexed and impact factor research journals\international conferences as well as 6 authored and 9 edited books on computer science. His areas of interest include wireless sensor network (WSN), Internet of Things, mobile application programming, ad hoc networks, cloud computing, big data, mobile computing, data mining and software engineering. Nguyen Gia Nhu received the PhD degree in computer science from Ha Noi University of Science, Vietnam National University, Vietnam. He is now the Vice Dean of Graduate School at Duy Tan University. He has more than 40 publications in reputed international conferences, journals and book chapter contributions. His research interests include algorithm theory, network optimization and wireless security. Jyotir Moy Chatterjee is working as an Assistant Professor in the Department of Computer Science and Engineering at GD-RCET, Bhilai, C.G, India. He received his M.Tech from KIIT University, Bhubaneswar, Odisha and B.Tech in Computer Science & Engineering from Dr. MGR Educational & Research Institute University, Chennai, (Tamil Nadu). His research interests include cloud computing, big data, privacy preservation and data mining.

List of Figures xiiList of Tables xvPreface xviiAcknowledgments xxiiiAcronyms xxvIntroduction xxvii1 Live Virtual Concept in Cloud Environment 11.1 Live Migration 21.1.1 Definition of Live Migration 21.1.2 Techniques for Live Migration 21.2 Issues with Migration 41.2.1 Application Performance Degradation 41.2.2 Network Congestion 41.2.3 Migration Time 51.3 Research on Live Migration 51.3.1 Sequencer (CQNCR) 51.3.2 The COMMA System 51.3.3 Clique Migration 61.3.4 Time-Bound Migration 61.3.5 Measuring Migration Impact 71.4 Total Migration Time 71.4.1 VM Traffic Impact 71.4.2 Bin Packing 81.5 Graph Partitioning 81.5.1 Learning Automata Partitioning 91.5.2 Advantages of Live Migration over WAN 111.6 Conclusion 12References 122 Live Virtual Machine Migration in Cloud 152.1 Introduction 162.1.1 Virtualization 162.1.2 Types of Virtual Machines 182.1.3 Virtual Machine Applications 182.2 Business Challenge 192.2.1 Dynamic Load Balancing 192.2.2 No VM Downtime During Maintenance 202.3 Virtual Machine Migration 202.3.1 Advantages of Virtualization 222.3.2 Components of Virtualization 222.3.3 Types of Virtualization 232.4 Virtualization System 262.4.1 Xen Hypervisor 262.4.2 KVM Hypervisor 272.4.3 OpenStack 302.4.4 Storage 312.4.5 Server Virtualization 332.5 Live Virtual Machine Migration 332.5.1 QEMU and KVM 342.5.2 Libvirt 352.6 Conclusion 36References 373 Attacks and Policies in Cloud Computing and Live Migration 393.1 Introduction to Cloud Computing 403.2 Common Types of Attacks and Policies 423.2.1 Buffer Overflows 423.2.2 Heap Overflows 423.2.3 Web-Based Attacks 433.2.4 DNS Attacks 473.2.5 Layer 3 Routing Attacks 483.2.6 ManintheMiddle Attack (MITM)3.3 Conclusion 50 References 50 494 Live Migration Security in Cloud 534.1 Cloud Security and Security Appliances 544.2 VMM in Clouds and Security Concerns 544.3 Software-Defined Networking 564.3.1 Firewall in Cloud and SDN 574.3.2 SDN and Floodlight Controllers 614.4 Distributed Messaging System 624.4.1 Approach 634.4.2 MigApp Design 634.5 Customized Testbed for Testing Migration Security in Cloud 634.5.1 Preliminaries 654.5.2 Testbed Description 664.6 A Case Study and Other Use Cases 674.6.1 Case Study: Firewall Rule Migration and Verification 684.6.2 Existing Security Issues in Cloud Scenarios 684.6.3 Authentication in Cloud 694.6.4 Hybrid Approaches for Security in Cloud Computing 714.6.5 Data Transfer Architecture in Cloud Computing 714.7 Conclusion 72References 725 Solution for Secure Live Migration 755.1 Detecting and Preventing Data Migrations to the Cloud 765.1.1 Internal Data Migrations 765.1.2 Movement to the Cloud 765.2 Protecting Data Moving to the Cloud 765.3 Application Security 775.4 Virtualization 785.5 Virtual Machine Guest Hardening 795.6 Security as a Service 825.6.1 Ubiquity of Security as a Service 835.6.2 Advantages of Implementing Security as a Service 855.6.3 Identity, Entitlement, and Access Management Services 875.7 Conclusion 93References 946 Dynamic Load Balancing Based on Live Migration 956.1 Introduction 966.2 Classification of Load Balancing Techniques 966.2.1 Static and Dynamic Scheduling 976.2.2 Load Rebalancing 976.3 Policy Engine 986.4 Load Balancing Algorithm 1006.5 Resource Load Balancing 1016.5.1 Server Load Metric 1026.5.2 System Imbalance Metric 1026.5.3 Other Key Parameters 1026.6 Load Balancers in Virtual Infrastructure Management Software 1036.7 VMware Distributed Resource Scheduler 1036.7.1 OpenNebula 1046.7.2 Scheduling Policies 1056.8 Conclusion 105References 1057 Live Migration in Cloud Data Center 1077.1 Definition of Data Center 1087.2 Data Center Traffic Characteristics 1107.3 Traffic Engineering for Data Centers 1117.4 Energy Efficiency in Cloud Data Centers 1137.5 Major Cause of Energy Waste 1137.5.1 Lack of a Standardized Metric ofServer Energy Efficiency7.5.2 Energy Efficient Solutions Are Still Not 113Widely Adopted 1147.6 Power Measurement and Modeling in Cloud 1147.7 Power Measurement Techniques 1147.7.1 Power Measurement for Servers 1147.7.2 Power Measurement for VMS 1157.7.3 Power and Energy Estimation Models 1157.7.4 Power and Energy Modeling for Servers 1157.7.5 Power Modeling for VMs 1167.7.6 Power Modeling for VM Migration 1167.7.7 Energy Efficiency Metrics 1177.8 Power Saving Policies in Cloud 1177.8.1 Dynamic Frequency and Voltage Scaling 1187.8.2 Powering Down 1187.8.3 EnergyAware Consolidation 1187.9 Conclusion 118References 1198 Trusted VM-vTPM Live Migration Protocol in Clouds 1218.1 Trusted Computing 1228.2 TPM Operations 1228.3 TPM Applications and Extensions 1238.4 TPM Use Cases 1248.5 State of the Art in Public Cloud Computing Security 1258.5.1 Cloud Management Interface 1258.5.2 Challenges in Securing the Virtualized Environment 1268.5.3 The Trust in TPM 1278.5.4 Challenges 1298.6 Launch and Migration of Virtual Machines 1308.6.1 Trusted Virtual Machines and VirtualMachine Managers 1308.6.2 Seeding Clouds with Trust Anchors 1318.6.3 Securely Launching Virtual Machines on Trustworthy Platforms in a Public Cloud 1318.7 Trusted VM Launch and Migration Protocol 1328.8 Conclusion 134References 1349 Lightweight Live Migration 1379.1 Introduction 1389.2 VM Checkpointing 1389.2.1 Checkpointing Virtual Cluster 1399.2.2 VM Resumption 1409.2.3 Migration without Hypervisor 1409.2.4 Adaptive Live Migration to Improve Load Balancing 1419.2.5 VM Disk Migrations 1429.3 Enhanced VM Live Migration 1439.4 VM Checkpointing Mechanisms 1449.5 Lightweight Live Migration for Solo VM 1459.5.1 Block Sharing and Hybrid Compression Support 1459.5.2 Architecture 1469.5.3 FGBI Execution Flow 1479.6 Lightweight Checkpointing 1489.6.1 High-Frequency Checkpointing Mechanism 1509.6.2 Distributed Checkpoint Algorithm in VPC 1509.7 StorageAdaptive Live Migration 1529.8 Conclusion 154References 15410 Virtual Machine Mobility with SelfMigration 15710.1 Checkpoints and Mobility 15810.2 Manual and Seamless Mobility 15810.3 Fine-and Coarse-Grained Mobility Models 15910.3.1 Data and Object Mobility 15910.3.2 Process Migration 16010.4 Migration Freeze Time 16010.5 Device Drivers 16110.5.1 Design Space 16210.5.2 In-Kernel Device Drivers 16210.5.3 Use of VMs for Driver Isolation 16410.5.4 Context Switching Overhead 16410.5.5 Restarting Device Drivers 16510.5.6 External Device State 16510.5.7 Type Safe Languages 16610.5.8 Software Fault Isolation 16610.6 Self-Migration 16710.6.1 Hosted Migration 16710.6.2 Self-Migration Prerequisites 16910.7 Conclusion 170References 17011 Different Approaches for Live Migration 17311.1 Virtualization 17411.1.1 Hardware-Assisted Virtualization 17411.1.2 Horizontal Scaling 17511.1.3 Vertical Scaling 17511.2 Types of Live Migration 17611.2.1 Cold Migration 17611.2.2 Suspend/Resume Migration 17611.2.3 Live VM Migration 17611.3 Live VM Migration Types 17711.3.1 Pre-Copy Live Migration 17711.3.2 Post-copy Live Migration 17811.3.3 Hybrid Live Migration 17811.4 Hybrid Live Migration 17911.4.1 Hybrid Approach for Live Migration 17911.4.2 Basic Hybrid Migration Algorithm 18011.5 Reliable Hybrid Live Migration 18011.5.1 Push Phase 18111.5.2 Stop-and-Copy Phase 18111.5.3 Pull Phase 18111.5.4 Network Buffering 18111.6 Conclusion 181References 18212 Migrating Security Policies in Cloud 18312.1 Cloud Computing 18412.2 Firewalls in Cloud and SDN 18712.3 Distributed Messaging System 19112.4 Migration Security in Cloud 19212.5 Conclusion 194References 19413 Case Study 19513.1 Kernel-Based Virtual Machine 19613.2 Xen 19613.3 Secure Data Analysis in GIS 19613.3.1 Database 19713.3.2 Data Mining and Techniques 19713.3.3 Distributed Database 19713.3.4 Spatial Data Mining 19813.3.5 Secure Multi-Party Computation 19813.3.6 Association Rule Mining Problem 19813.3.7 Distributed Association Ruling 19913.3.8 Data Analysis in GIS System13.4 Emergence of Green Computing in Modern Computing Environment 20013.5 Green Computing 20313.6 Conclusion 204References 205