
Cloud Services, Networking, and Management
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Each chapter of the book is a separate self-contained part. The length of each chapter is adequately selected, while the balance between an introduction for beginners and details for advanced readers is excellently preserved. For a majority of the covered topics, a comprehensive survey and thoughtful taxonomy are provided. The presented issues are followed by the exemplary solutions, which are not only conceptual, but very often describe practical deployments. Furthermore, the reference lists are complete, while indicated directions for further studies are relevant and valuable.......Summarizing, I recommend this book as a source of very relevant and valuable information about popular and emerging cloud-related topics. An additional advantage is that security and energy efficiency are also addressed. - (IEEE Communication Magazine- Nov 2016)More details
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Content
Preface xiii
Contributors xvii
Part I Basic Concepts and Enabling Technologies 1
1 Cloud Architectures, Networks, Services, and Management 3
1.1 Introduction 3
1.2 Part I: Introduction to Cloud Computing 4
1.3 Part II: Research Challenges-The Chapters in This Book 14
1.4 Conclusion 21
References 21
2 Virtualization in the Cloud 23
2.1 The Need for Virtualization Management in the Cloud 23
2.2 Basic Concepts 25
2.3 Virtualized Elements 26
2.4 Virtualization Operations 29
2.5 Interfaces for Virtualization Management 30
2.6 Tools and Systems 34
2.7 Challenges 40
References 44
3 Virtual Machine Migration 49
3.1 Introduction 49
3.2 VM Migration 51
3.3 Virtual Network Migration without Packet Loss 59
3.4 Security of Virtual Environments 61
3.5 Future Directions 66
3.6 Conclusion 68
References 68
Part II Cloud Networking and Communications 73
4 Datacenter Networks and Relevant Standards 75
4.1 Overview 75
4.2 Topologies 76
4.3 Network Expansion 82
4.4 Traffic 85
4.5 Routing 89
4.6 Addressing 93
4.7 Research Challenges 96
4.8 Summary 98
References 99
5 Inter-Data-Center Networks with Minimum Operational Costs 105
5.1 Introduction 105
5.2 Inter-Data-Center Network Virtualization 108
5.3 IDC Network Design with Minimum Electric Bills 115
5.4 Inter-Data-Center Network Design with Minimum Downtime Penalties 120
5.5 Overcoming Energy versus Resilience Trade-Off 123
5.6 Summary and Discussions 124
References 126
6 Openflow and SDN for Clouds 129
6.1 Introduction 129
6.2 SDN, Cloud Computing, and Virtualization Challenges 130
6.3 Software-Defined Networking 132
6.4 Overview of Cloud Computing and OpenStack 138
6.5 SDN for Cloud Computing 142
6.6 Combining OpenFlow and OpenStack with OpenDaylight 145
6.7 Software-Defined Infrastructures 149
6.8 Research Trends and Challenges 150
6.9 Concluding Remarks 151
References 151
7 Mobile Cloud Computing 153
7.1 Introduction 153
7.2 Mobile Cloud Computing 155
7.3 Risks in MCC 163
7.4 Risk Management for MCC 177
7.5 Conclusions 184
References 186
Part III Cloud Management 191
8 Energy Consumption Optimization in Cloud Data Centers 193
8.1 Introduction 193
8.2 Energy Consumption in Data Centers: Components and Models 195
8.3 Energy Efficient System-Level Optimization of Data Centers 198
8.4 Conclusions and Open Challenges 210
References 211
9 Performance Management and Monitoring 217
9.1 Introduction 217
9.2 Background Concepts 219
9.3 Related Work 221
9.4 X-Cloud Application Management Platform 222
9.5 Implementation 229
9.6 Experiments and a Case Study 232
9.7 Challenges in Management on Heterogeneous Clouds 238
9.8 Conclusion 239
References 240
10 Resource Management and Scheduling 243
10.1 Introduction 243
10.2 Basic Concepts 244
10.3 Applications 248
10.4 Problem Definition 249
10.5 Resource Management and Scheduling in Clouds 254
10.6 Challenges and Perspectives 262
10.7 Conclusion 264
References 264
11 Cloud Security 269
11.1 Introduction 270
11.2 Technical Background 273
11.3 Existing Solutions 274
11.4 Transforming to the New IDPS Cloud Security Solutions 278
11.5 FlowIPS: Design and Implementation 279
11.6 FlowIPS vs Snort/Iptables IPS 282
11.7 Network Reconfiguration 284
11.8 Performance Comparison 288
11.9 Open Issues and Future Work 290
11.10 Conclusion 291
References 291
12 Survivability and Fault Tolerance in the Cloud 295
12.1 Introduction 295
12.2 Background 296
12.3 Failure Characterization in Cloud Environments 298
12.4 Availability-Aware Resource Allocation Schemes 299
12.5 Conclusion 307
References 307
Part IV Cloud Applications and Services 309
13 Scientific Applications on Clouds 311
13.1 Introduction 311
13.2 Background Information 313
13.3 Related Work 313
13.4 IWIR Workflow Model 314
13.5 Amazon SWF Background 315
13.6 RainCloud Workflow 317
13.7 IWIR-to-SWF Conversion 319
13.8 Experiments 324
13.9 Open Challenges 328
13.10 Conclusion 329
References 330
14 Interactive Multimedia Applications on Clouds 333
14.1 Introduction 333
14.2 Delivery Models for Interactive Multimedia Services 335
14.3 Cloud Gaming 339
14.4 UGC Live Streaming 345
14.5 Time-Shifting Video Streaming 351
14.6 Open Challenges 353
14.7 Conclusion 354
References 355
15 Big Data on Clouds (BDOC) 361
15.1 Introduction 361
15.2 Historical Perspective and State of the Art 362
15.3 Clouds-Supply and Demand of Big Data 364
15.4 Emerging Business Applications 365
15.5 Cloud and Service Availability 368
15.6 BDOC Security Issues 372
15.7 BDOC Legal Issues 379
15.8 Enabling Future Success-Stem Cultivation and Outreach 384
15.9 Open Challenges and Future Directions 385
15.10 Conclusions 388
References 388
Index 393
1
CLOUD ARCHITECTURES, NETWORKS, SERVICES, AND MANAGEMENT
Raouf Boutaba1 and Nelson L. S. da Fonseca2
1 D.R. Cheriton School of Computer Science, University of Waterloo, Waterloo, Ontario, Canada
2 Institute of Computing, State University of Campinas, Campinas, São Paulo, Brazil
1.1 INTRODUCTION
With the wide availability of high-bandwidth, low-latency network connectivity, the Internet has enabled the delivery of rich services such as social networking, content delivery, and e-commerce at unprecedented scales. This technological trend has led to the development of cloud computing, a paradigm that harnesses the massive capacities of data centers to support the delivery of online services in a cost-effective manner. In a cloud computing environment, the traditional role of service providers is divided into two: cloud providers who own the physical data center and lease resources (e.g., virtual machines or VMs) to service providers; and service providers who use resources leased by cloud providers to execute applications. By leveraging the economies-of-scale of data centers, cloud computing can provide significant reduction in operational expenditure. At the same time, it also supports new applications such as big-data analytics (e.g., MapReduce [1]) that process massive volumes of data in a scalable and efficient fashion. The rise of cloud computing has made a profound impact on the development of the IT industry in recent years. While large companies like Google, Amazon, Facebook, and Microsoft have developed their own cloud platforms and technologies, many small companies are also embracing cloud computing by leveraging open-source software and deploying services in public clouds.
However, despite the wide adoption of cloud computing in the industry, the current cloud technologies are still far from unleashing their full potential. In fact, cloud computing was known as a buzzword for several years, and many IT companies were uncertain about how to make successful investment in cloud computing. Fortunately, with the significant attraction from both industry and academia, cloud computing is evolving rapidly, with advancements in almost all aspects, ranging from data center architectural design, scheduling and resource management, server and network virtualization, data storage, programming frameworks, energy management, pricing, service connectivity to security, and privacy.
The goal of this chapter is to provide a general introduction to cloud networking, services, and management. We first provide an overview of cloud computing, describing its key driving forces, characteristics and enabling technologies. Then, we focus on the different characteristics of cloud computing systems and key research challenges that are covered in the subsequent 14 chapters of this book. Specifically, the chapters delve into several topics related to cloud services, networking and management including virtualization and software-defined network technologies, intra- and inter- data center network architectures, resource, performance and energy management in the cloud, survivability, fault tolerance and security, mobile cloud computing, and cloud applications notably big data, scientific, and multimedia applications.
1.2 PART I: INTRODUCTION TO CLOUD COMPUTING
1.2.1 What Is Cloud Computing?
Despite being widely used in different contexts, a precise definition of cloud computing is rather elusive. In the past, there were dozens of attempts trying to provide an accurate yet concise definition of cloud computing [2]. However, most of the proposed definitions only focus on particular aspects of cloud computing, such as the business model and technology (e.g., virtualization) used in cloud environments. Due to lack of consensus on how to define cloud computing, for years cloud computing was considered a buzz word or a marketing hype in order to get businesses to invest more in their IT infrastructures. The National Institute of Standards and Technology (NIST) provided a relatively standard and widely accepted definition of cloud computing as follows: "cloud computing is a model for enabling ubiquitous, convenient, on-demand network access to a shared pool of configurable computing resources (e.g., networks, servers, storage, applications, and services) that can be rapidly provisioned and released with minimal management effort or service provider interaction." [3]
NIST further defined five essential characteristics, three service models, and four deployment models, for cloud computing. The five essential characteristics include the following:
- On-demand self-service, which states that a consumer (e.g., a service provider) can acquire resources based on service demand;
- Broad network access, which states that cloud services can be accessed remotely from heterogeneous client platforms (e.g., mobile phones);
- Resource pooling, where resources are pooled and shared by consumers in a multi-tenant fashion;
- Rapid elasticity, which states that cloud resources can be rapidly provisioned and released with minimal human involvement;
- Measured service, which states that resources are controlled (and possibly priced) by leveraging a metering capability (e.g., pay-per-use) that is appropriate to the type of the service.
These characteristics provide a relatively accurate picture of what cloud computing systems should look like. It should be mentioned that not every cloud computing system exhibits all five characteristics listed earlier. For example, in a private cloud, where the service provider owns the physical data center, the metering capability may not be necessary because there is no need to limit resource usage of the service unless it is reaching data center capacity limits. However, despite the definition and aforementioned characteristics, cloud computing can still be realized in a large number of ways, and hence one may argue the definition is still not precise enough. Today, cloud computing commonly refers to a computing model where services are hosted using resources in data centers and delivered to end users over the Internet. In our opinion, since cloud computing technologies are still evolving, finding the precise definition of cloud computing at the current moment may not be the right approach. Perhaps once the technologies have reached maturity, the true definition will naturally emerge.
1.2.2 Why Cloud Computing?
In this section, we present the motivation behind the development of cloud computing. We will also compare cloud computing with other parallel and distributed computing models and highlight their differences.
1.2.2.1 Key Driving Forces.
There are several driving forces behind the success of cloud computing. The increasing demand for large-scale computation and big data analytics and economics are the most important ones. But other factors such as easy access to computation and storage, flexibility in resource allocations, and scalability play important roles.
Large-scale computation and big data: Recent years have witnessed the rise of Internet-scale applications. These applications range from social networks (e.g., facebook, twitter), video applications (e.g., Netflix, youtube), enterprise applications (e.g., SalesForce, Microsoft CRM) to personal applications (e.g., iCloud, Dropbox). These applications are commonly accessed by large numbers of users over the Internet. They are extremely large scale and resource intensive. Furthermore, they often have high performance requirements such as response time. Supporting these applications requires extremely large-scale infrastructures. For instance, Google has hundreds of compute clusters deployed worldwide with hundreds of thousands of servers. Another salient characteristic is that these applications also require access to huge volumes of data. For instance, Facebook stores tens of petabytes of data and processes over a hundred terabytes per day. Scientific applications (e.g., brain image processing, astrophysics, ocean monitoring, and DNA analysis) are more and more deployed in the cloud. Cloud computing emerged in this context as a computing model designed for running large applications in a scalable and cost-efficient manner by harnessing massive resource capacities in data centers and by sharing the data center resources among applications in an on-demand fashion.
Economics: To support large-scale computation, cloud providers rely on inexpensive commodity hardware offering better scalability and performance/price ratio than supercomputers. By deploying a very large number of commodity machines, they leverage economies of scale bringing per unit cost down and allowing for incremental growth. On the other hand, cloud customers such as small and medium enterprises, which outsource their IT infrastructure to the cloud, avoid upfront infrastructure investment cost and instead benefit from a pay-as-you-go pricing and billing model. They can deploy their services in the cloud and make them quickly available to their own customers resulting in short time to market. They can start small and scale up and down their infrastructure based on their customers demand and pay based on usage.
Scalability: By harnessing huge computing and storage capabilities, cloud computing gives customers the illusion of infinite resources on demand. Customers can start small and scale up and down resources as needed.
Flexibility: Cloud computing is highly flexible. It allows customers to specify their resource requirements in terms of CPU cores, memory, storage, and networking capabilities. Customers are also offered the...
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