Peering Carrier Ethernet Networks begins by providing background information on the evolution of important concepts and building blocks that have led to the current state of high bandwidth and high performance Ethernet technology in order to support current and emerging customer applications. The background information covered includes an overview of Public Switched Telephone Networks (PSTN) to describe circuit switching, multiplexing, and voice digitization that lead to the development of T1/T3 and SONET/SDH for transport. It interweaves these developments with changes in the regulatory regime. Additional coverage includes Carrier Ethernet networks' technical standards, which describe how service providers can offer services to off-net customers using peered Carrier Ethernet networks and a description of the taxonomy of customers and their current and emerging applications at Layer 2 and Layer 3 on peered Carrier Ethernet networks. The book concludes by describing next steps in Ethernet technology to meet growing demands and emerging trends.

Cyber-Physical Systems: Foundations, Principles and Applications explores the core system science perspective needed to design and build complex cyber-physical systems. Using Systems Science's underlying theories, such as probability theory, decision theory, game theory, organizational sociology, behavioral economics, and cognitive psychology, the book addresses foundational issues central across CPS applications, including System Design -- How to design CPS to be safe, secure, and resilient in rapidly evolving environments, System Verification -- How to develop effective metrics and methods to verify and certify large and complex CPS, Real-time Control and Adaptation -- How to achieve real-time dynamic control and behavior adaptation in a diverse environments, such as clouds and in network-challenged spaces, Manufacturing -- How to harness communication, computation, and control for developing new products, reducing product concepts to realizable designs, and producing integrated software-hardware systems at a pace far exceeding today's timeline. The book is part of the Intelligent Data-Centric Systems: Sensor-Collected Intelligence series edited by Fatos Xhafa, Technical University of Catalonia. Indexing: The books of this series are submitted to EI-Compendex and SCOPUS

This book has a focus on the development and deployment of the Industrial Internet of Things (IIoT) paradigm, discussing frameworks, methodologies, benefits and limitations, as well as providing case studies of employing the IoT vision in the industrial domain. IIoT is becoming an attractive business reality for many organisations such as manufacturing, logistics, oil and gas, energy and other utilities, mining, aviation, and many more. The opportunities for this paradigm are huge, and according to one report, the IIoT market is predicted to reach $125 billion by 2021. The driving philosophy behind the IIoT is that smart machines are better than humans at accurately capturing, analysing and communicating real-time data. The underlying technologies include distributed computing, machine learning, artificial intelligence, and machine-to-machine communication, with a typical IIoT system consisting of intelligent systems (applications, controllers, sensors, and security mechanisms), data communication infrastructure (cloud computing, edge computing, etc.), data analytics (to support business intelligence and corporate decision making), and most importantly the human element. The promised benefits of the IIoT include enhanced safety, better reliability, smart metering, inventory management, equipment tracking, and facilities management. There are, however, numerous issues that are also becoming the focus of active research, such as concerns regarding service availability, data security, and device communication. Lack of ubiquitous interoperability between heterogeneous devices is also a major concern. This book intends to fill a gap in the IIoT literature by providing the scientific contributions and latest developments from researchers and practitioners of international repute, focusing on frameworks, methodologies, benefits, and inherent issues/barriers to connected environments, especially in industrial settings. The intended audience includes network specialists, hardware engineers, and security experts who wish to adopt newer approaches for device connectivity, IoT security, and sensor-based devices design. University level students, researchers and practitioners will also find the latest innovation in technology and newer approaches relevant to the IIoT from a distributed computing perspective.

This handbook is organized under three major parts. The first part of this handbook deals with multimedia security for emerging applications. The chapters include basic concepts of multimedia tools and applications, biological and behavioral biometrics, effective multimedia encryption and secure watermarking techniques for emerging applications, an adaptive face identification approach for android mobile devices, and multimedia using chaotic and perceptual hashing function. The second part of this handbook focuses on multimedia processing for various potential applications. The chapter includes a detail survey of image processing based automated glaucoma detection techniques and role of de-noising, recent study of dictionary learning based image reconstruction techniques for analyzing the big medical data, brief introduction of quantum image processing and it applications, a segmentation-less efficient Alzheimer detection approach, object recognition, image enhancements and de-noising techniques for emerging applications, improved performance of image compression approach, and automated detection of eye related diseases using digital image processing. The third part of this handbook introduces multimedia applications. The chapter includes the extensive survey on the role of multimedia in medicine and multimedia forensics classification, a finger based authentication system for e-health security, analysis of recently developed deep learning techniques for emotion and activity recognition. Further, the book introduce a case study on change of ECG according to time for user identification, role of multimedia in big data, cloud computing, the Internet of things (IoT) and blockchain environment in detail for real life applications. This handbook targets researchers, policy makers, programmers and industry professionals in creating new knowledge for developing efficient techniques/framework for multimedia applications. Advanced level students studying computer science, specifically security and multimedia will find this book useful as a reference.

This handbook introduces the basic principles and fundamentals of cyber security towards establishing an understanding of how to protect computers from hackers and adversaries. The highly informative subject matter of this handbook, includes various concepts, models, and terminologies along with examples and illustrations to demonstrate substantial technical details of the field. It motivates the readers to exercise better protection and defense mechanisms to deal with attackers and mitigate the situation. This handbook also outlines some of the exciting areas of future research where the existing approaches can be implemented. Exponential increase in the use of computers as a means of storing and retrieving security-intensive information, requires placement of adequate security measures to safeguard the entire computing and communication scenario. With the advent of Internet and its underlying technologies, information security aspects are becoming a prime concern towards protecting the networks and the cyber ecosystem from variety of threats, which is illustrated in this handbook. This handbook primarily targets professionals in security, privacy and trust to use and improve the reliability of businesses in a distributed manner, as well as computer scientists and software developers, who are seeking to carry out research and develop software in information and cyber security. Researchers and advanced-level students in computer science will also benefit from this reference.

This is the first book describing cable networks, services, and their management in greater detail by thirteen experts in various fields covering network architectures and services, operations, administration, maintenance, provisioning, troubleshooting (OAMPT) for residential services; network architectures, services, and OAMPT for business services; Software Defined Networks (SDN) and Virtualization concepts Comprehensive reference book useful for people working for a multiple systems operator Includes chapter introductions Written by 13 experts in various fields such as network services and soft defined networks

This book introduces concepts and technologies of Intelligent Transportation Systems (ITS). It describes state of the art safety communication protocol called Dedicated Short Range Communication (DSRC), currently being considered for adoption by the USDOT and automotive industry in the US. However, the principles of this book are applicable even if the underlying physical layer protocol of V2X changes in the future, e.g. V2X changes from DSRC to cellular-based connectivity. Fundamental ITS concepts include topics like global positioning system; Vehicle to Vehicle (V2V), Vehicle to Pedestrian (V2P), and Vehicle to Infrastructure (V2I) communications; human-machine interface; and security and privacy. Fundamental concepts are sometimes followed by the real-life test experimental results (such as in V2P Chapter) and description of the performance metrics used to evaluate the results. This book also describes equations and math used in the development of the individual parts of the system. This book surveys current and previous publications for trending research in the ITS domain. It also covers state of the art standards that are in place for the DSRC in the US, starting from the application layer defined in SAE J2735 all the way to physical layer defined in IEEE 802.11. The authors provide a detailed discussion on what is needed to extend the current standards to accommodate future needs of the vehicle communications, such as needs for future autonomous vehicles. Programs and code examples accompany appropriate chapters, for example, after describing remote vehicle target classification function a pseudo code and description is provided. In addition, the book discusses current topics of the technology such as spectrum sharing, simulation, security, and privacy. The intended audience for this book includes engineering graduate students, automotive professionals/engineers, researchers and technology enthusiasts.

This book covers and makes four major contributions: 1) analyzing and surveying the pros and cons of current approaches for identifying rumor sources on complex networks; 2) proposing a novel approach to identify rumor sources in time-varying networks; 3) developing a fast approach to identify multiple rumor sources; 4) proposing a community-based method to overcome the scalability issue in this research area. These contributions enable rumor source identification to be applied effectively in real-world networks, and eventually diminish rumor damages, which the authors rigorously illustrate in this book. In the modern world, the ubiquity of networks has made us vulnerable to various risks. For instance, viruses propagate throughout the Internet and infect millions of computers. Misinformation spreads incredibly fast in online social networks, such as Facebook and Twitter. Infectious diseases, such as SARS, H1N1 or Ebola, have spread geographically and killed hundreds of thousands people. In essence, all of these situations can be modeled as a rumor spreading through a network, where the goal is to find the source of the rumor so as to control and prevent network risks. So far, extensive work has been done to develop new approaches to effectively identify rumor sources. However, current approaches still suffer from critical weaknesses. The most serious one is the complex spatiotemporal diffusion process of rumors in time-varying networks, which is the bottleneck of current approaches. The second problem lies in the expensively computational complexity of identifying multiple rumor sources. The third important issue is the huge scale of the underlying networks, which makes it difficult to develop efficient strategies to quickly and accurately identify rumor sources. These weaknesses prevent rumor source identification from being applied in a broader range of real-world applications. This book aims to analyze and address these issues to make rumor source identification more effective and applicable in the real world. The authors propose a novel reverse dissemination strategy to narrow down the scale of suspicious sources, which dramatically promotes the efficiency of their method. The authors then develop a Maximum-likelihood estimator, which can pin point the true source from the suspects with high accuracy. For the scalability issue in rumor source identification, the authors explore sensor techniques and develop a community structure based method. Then the authors take the advantage of the linear correlation between rumor spreading time and infection distance, and develop a fast method to locate the rumor diffusion source. Theoretical analysis proves the efficiency of the proposed method, and the experiment results verify the significant advantages of the proposed method in large-scale networks. This book targets graduate and post-graduate students studying computer science and networking. Researchers and professionals working in network security, propagation models and other related topics, will also be interested in this book.

This book provides a comprehensive introduction to applying compressive sensing to improve data quality in the context of mobile crowdsensing. It addresses the following main topics: recovering missing data, efficiently collecting data, preserving user privacy, and detecting false data. Mobile crowdsensing, as an emerging sensing paradigm, enables the masses to take part in data collection tasks with the aid of powerful mobile devices. However, mobile crowdsensing platforms have yet to be widely adopted in practice, the major concern being the quality of the data collected. There are numerous causes: some locations may generate redundant data, while others may not be covered at all, since the participants are rarely systematically coordinated; privacy is a concern for some people, who don't wish to share their real-time locations, and therefore some key information may be missing; further, some participants may upload fake data in order to fraudulently gain rewards. To address these problematic aspects, compressive sensing, which works by accurately recovering a sparse signal using very few samples, has proven to offer an effective solution.

This classroom-tested textbook describes the design and implementation of software for distributed real-time systems, using a bottom-up approach. The text addresses common challenges faced in software projects involving real-time systems, and presents a novel method for simply and effectively performing all of the software engineering steps. Each chapter opens with a discussion of the core concepts, together with a review of the relevant methods and available software. This is then followed with a description of the implementation of the concepts in a sample kernel, complete with executable code. Topics and features: introduces the fundamentals of real-time systems, including real-time architecture and distributed real-time systems; presents a focus on the real-time operating system, covering the concepts of task, memory, and input/output management; provides a detailed step-by-step construction of a real-time operating system kernel, which is then used to test various higher level implementations; describes periodic and aperiodic scheduling, resource management, and distributed scheduling; reviews the process of application design from high-level design methods to low-level details of design and implementation; surveys real-time programming languages and fault tolerance techniques; includes end-of-chapter review questions, extensive C code, numerous examples, and a case study implementing the methods in real-world applications; supplies additional material at an associated website. Requiring only a basic background in computer architecture and operating systems, this practically-oriented work is an invaluable study aid for senior undergraduate and graduate-level students of electrical and computer engineering, and computer science. The text will also serve as a useful general reference for researchers interested in real-time systems.

This book uses motivating examples and real-life attack scenarios to introduce readers to the general concept of fault attacks in cryptography. It offers insights into how the fault tolerance theories developed in the book can actually be implemented, with a particular focus on a wide spectrum of fault models and practical fault injection techniques, ranging from simple, low-cost techniques to high-end equipment-based methods. It then individually examines fault attack vulnerabilities in symmetric, asymmetric and authenticated encryption systems. This is followed by extensive coverage of countermeasure techniques and fault tolerant architectures that attempt to thwart such vulnerabilities. Lastly, it presents a case study of a comprehensive FPGA-based fault tolerant architecture for AES-128, which brings together of a number of the fault tolerance techniques presented. It concludes with a discussion on how fault tolerance can be combined with side channel security to achieve protection against implementation-based attacks. The text is supported by illustrative diagrams, algorithms, tables and diagrams presenting real-world experimental results.

This book presents a design methodology that is practically applicable to the architectural design of a broad range of systems. It is based on fundamental design concepts to conceive and specify the required functional properties of a system, while abstracting from the specific implementation functions and technologies that can be chosen to build the system. Abstraction and precision are indispensable when it comes to understanding complex systems and precisely creating and representing them at a high functional level. Once understood, these concepts appear natural, self-evident and extremely powerful, since they can directly, precisely and concisely reflect what is considered essential for the functional behavior of a system. The first two chapters present the global views on how to design systems and how to interpret terms and meta-concepts. This informal introduction provides the general context for the remainder of the book. On a more formal level, Chapters 3 through 6 present the main basic design concepts, illustrating them with examples. Language notations are introduced along with the basic design concepts. Lastly, Chapters 7 to 12 discuss the more intricate basic design concepts of interactive systems by focusing on their common functional goal. These chapters are recommended to readers who have a particular interest in the design of protocols and interfaces for various systems. The didactic approach makes it suitable for graduate students who want to develop insights into and skills in developing complex systems, as well as practitioners in industry and large organizations who are responsible for the design and development of large and complex systems. It includes numerous tangible examples from various fields, and several appealing exercises with their solutions.

This book investigates and reviews recent advanced techniques and important applications in vehicular communications and networking (VCN) from a novel perspective of the combination and integration of VCN and connected vehicles, which provides a significant scientific and technical support for future 5G-based VCN. 5G-Enabled Vehicular Communications and Networking introduces vehicular channel characteristics, reviews current channel modeling approaches, and then provides a new generic geometry-based stochastic modeling approach for vehicle-to-everything (V2X) communications. The investigation of vehicular channel measurements and modeling provides fundamental supports for the VCN system design. Then, this book investigates VCN-vehicle combination from PHY and MAC layers, respectively. As for the PHY layer, many advanced techniques that can be effectively applied in VCN to counter the PHY challenges are introduced, including novel ICI cancellation methods, index modulated OFDM, differential spatial modulation, and energy harvesting relaying. As for the MAC layer, distributed and centralized MAC designs are analyzed and compared in terms of feasibility and availability. Specifically, distributed congestion control, D2D-enabled vehicular communications, and centralized data dissemination scheduling are elaborated, which can significantly improve the network performance in vehicular networks. Finally, considering VCN-vehicle integration, this book introduces several hot-topic applications in vehicular networks, including electric vehicles, distributed data storage, unmanned aerial vehicles, and security and privacy, which indicates the significance and development value of VCN-vehicle integration in future vehicular networks and our daily life. The primary audience for this book includes professionals and researchers working in the field of vehicular communications, intelligent transportation systems (ITS), and Internet of vehicles (IoV). Advanced level students studying electrical engineering will also find this book useful as a secondary textbook for related courses.

This book showcases new and innovative approaches to biometric data capture and analysis, focusing especially on those that are characterized by non-intrusiveness, reliable prediction algorithms, and high user acceptance. It comprises the peer-reviewed papers from the international workshop on the subject that was held in Ancona, Italy, in October 2014 and featured sessions on ICT for health care, biometric data in automotive and home applications, embedded systems for biometric data analysis, biometric data analysis: EMG and ECG, and ICT for gait analysis. The background to the book is the challenge posed by the prevention and treatment of common, widespread chronic diseases in modern, aging societies. Capture of biometric data is a cornerstone for any analysis and treatment strategy. The latest advances in sensor technology allow accurate data measurement in a non-intrusive way, and in many cases it is necessary to provide online monitoring and real-time data capturing to support a patient's prevention plans or to allow medical professionals to access the patient's current status. This book will be of value to all with an interest in this expanding field.

This volume is focused on the emerging concept of Collaborative Innovation Networks (COINs). COINs are at the core of collaborative knowledge networks, distributed communities taking advantage of the wide connectivity and the support of communication technologies, spanning beyond the organizational perimeter of companies on a global scale. It includes the refereed conference papers from the 6th International Conference on COINs, June 8-11, 2016, in Rome, Italy. It includes papers for both application areas of COINs, (1) optimizing organizational creativity and performance, and (2) discovering and predicting new trends by identifying COINs on the Web through online social media analysis. Papers at COINs16 combine a wide range of interdisciplinary fields such as social network analysis, group dynamics, design and visualization, information systems and the psychology and sociality of collaboration, and intercultural analysis through the lens of online social media. They will cover most recent advances in areas from leadership and collaboration, trend prediction and data mining, to social competence and Internet communication.

This work makes major contributions to the thriving area of social, communication, and distributed networks by introducing novel methodologies and tools toward the study of the evolutionary behaviors of these networks, as well as their computational complexity and rates of convergence. By departing from the classical approaches and results in the literature, this work shows that it is possible to handle more complex and realistic nonlinear models where either the traditional approaches fail or lead to weak results. The author also develops several easily implementable algorithms, delivering excellent performance guarantees while running faster than those that exist in the literature. The study undertaken and the approaches adopted enable the analysis of the evolution of several different types of social and distributed networks, with the potential to apply to and resolve several other outstanding issues in such networks.

This proceeding features papers discussing big data innovation for sustainable cognitive computing. The papers feature detail on cognitive computing and its self-learning systems that use data mining, pattern recognition and natural language processing (NLP) to mirror the way the human brain works. This international conference focuses on cognitive computing technologies, from knowledge representation techniques and natural language processing algorithms to dynamic learning approaches. Topics covered include Data Science for Cognitive Analysis, Real-Time Ubiquitous Data Science, Platform for Privacy Preserving Data Science, and Internet-Based Cognitive Platform. The EAI International Conference on Big Data Innovation for Sustainable Cognitive Computing (BDCC 2018), took place on 13 - 15 December 2018 in Coimbatore, India.

This book presents the design of delay-efficient packet schedulers for heterogeneous M2M uplink traffic classified into several classes, based on packet delay requirements, payload size, arrival process, etc. Specifically, the authors use tools from queuing theory to determine the delay-optimal scheduling policy. The proposed packet schedulers are designed for a generic M2M architecture and thus equally applicable to any M2M application. Additionally, due to their low implementation complexity and excellent delay-performance, they authors show how they are also well-suited for practical M2M systems. The book pertains primarily to real-time process scheduler experts in industry/academia and graduate students whose research deals with designing Quality-of-Service-aware packet schedulers for M2M packet schedulers over existing and future cellular infrastructure. Presents queuing theoretic analysis and optimization techniques used to design proposed packet scheduling strategies; Provides utility functions to precisely model diverse delay requirements, which lends itself to formulation of utility-maximization problems for determining the delay- or utility-optimal packet scheduler; Includes detail on low implementation complexity of the proposed scheduler by using iterative and distributed optimization techniques.

This book introduces a number of recent developments on connectivity of communication networks, ranging from connectivity of large static networks and connectivity of highly dynamic networks to connectivity of small to medium sized networks. This book also introduces some applications of connectivity studies in network optimization, in network localization, and in estimating distances between nodes. The book starts with an overview of the fundamental concepts, models, tools, and methodologies used for connectivity studies. The rest of the chapters are divided into four parts: connectivity of large static networks, connectivity of highly dynamic networks, connectivity of small to medium sized networks, and applications of connectivity studies.

This book provides an overview of the problems involved in engineering scalable, elastic, and cost-efficient cloud computing services and describes the CloudScale method - a description of rescuing tools and the required steps to exploit these tools. It allows readers to analyze the scalability problem in detail and identify scalability anti-patterns and bottlenecks within an application. With the CloudScale method, software architects can analyze both existing and planned IT services. The method allows readers to answer questions like: * With an increasing number of users, can my service still deliver acceptable quality of service? * What if each user uses the service more intensively? Can my service still handle it with acceptable quality of service? * What if the number of users suddenly increases? Will my service still be able to handle it? * Will my service be cost-efficient? First the book addresses the importance of scalability, elasticity, and cost-efficiency as vital quality-related attributes of modern cloud computing applications. Following a brief overview of CloudScale, cloud computing applications are then introduced in detail and the aspects that need to be captured in models of such applications are discussed. In CloudScale, these aspects are captured in instances of the ScaleDL modeling language. Subsequently, the book describes the forward engineering part of CloudScale, which is applicable when developing a new service. It also outlines the reverse and reengineering parts of CloudScale, which come into play when an existing (legacy) service is modified. Lastly, the book directly focuses on the needs of both business-oriented and technical managers by providing guidance on all steps of implementing CloudScale as well as making decisions during that implementation. The demonstrators and reference projects described serve as a valuable starting point for learning from experience. This book is meant for all stakeholders interested in delivering scalable, elastic, and cost-efficient cloud computing applications: managers, product owners, software architects and developers alike. With this book, they can both see the overall picture as well as dive into issues of particular interest.

This book introduces the development of self-interference (SI)-cancellation techniques for full-duplex wireless communication systems. The authors rely on estimation theory and signal processing to develop SI-cancellation algorithms by generating an estimate of the received SI and subtracting it from the received signal. The authors also cover two new SI-cancellation methods using the new concept of active signal injection (ASI) for full-duplex MIMO-OFDM systems. The ASI approach adds an appropriate cancelling signal to each transmitted signal such that the combined signals from transmit antennas attenuate the SI at the receive antennas. The authors illustrate that the SI-pre-cancelling signal does not affect the data-bearing signal. This book is for researchers and professionals working in wireless communications and engineers willing to understand the challenges of deploying full-duplex and practical solutions to implement a full-duplex system. Advanced-level students in electrical engineering and computer science studying wireless communications will also find this book useful as a secondary textbook.

This book presents state-of-the-art research on robust resource allocation in current and future wireless networks. The authors describe the nominal resource allocation problems in wireless networks and explain why introducing robustness in such networks is desirable. Then, depending on the objectives of the problem, namely maximizing the social utility or the per-user utility, cooperative or competitive approaches are explained and their corresponding robust problems are considered in detail. For each approach, the costs and benefits of robust schemes are discussed and the algorithms for reducing their costs and improving their benefits are presented. Considering the fact that such problems are inherently non-convex and intractable, a taxonomy of different relaxation techniques is presented, and applications of such techniques are shown via several examples throughout the book. Finally, the authors argue that resource allocation continues to be an important issue in future wireless networks, and propose specific problems for future research.

This book provides a general and comprehensible overview of imbalanced learning. It contains a formal description of a problem, and focuses on its main features, and the most relevant proposed solutions. Additionally, it considers the different scenarios in Data Science for which the imbalanced classification can create a real challenge. This book stresses the gap with standard classification tasks by reviewing the case studies and ad-hoc performance metrics that are applied in this area. It also covers the different approaches that have been traditionally applied to address the binary skewed class distribution. Specifically, it reviews cost-sensitive learning, data-level preprocessing methods and algorithm-level solutions, taking also into account those ensemble-learning solutions that embed any of the former alternatives. Furthermore, it focuses on the extension of the problem for multi-class problems, where the former classical methods are no longer to be applied in a straightforward way. This book also focuses on the data intrinsic characteristics that are the main causes which, added to the uneven class distribution, truly hinders the performance of classification algorithms in this scenario. Then, some notes on data reduction are provided in order to understand the advantages related to the use of this type of approaches. Finally this book introduces some novel areas of study that are gathering a deeper attention on the imbalanced data issue. Specifically, it considers the classification of data streams, non-classical classification problems, and the scalability related to Big Data. Examples of software libraries and modules to address imbalanced classification are provided. This book is highly suitable for technical professionals, senior undergraduate and graduate students in the areas of data science, computer science and engineering. It will also be useful for scientists and researchers to gain insight on the current developments in this area of study, as well as future research directions.

Cloud service benchmarking can provide important, sometimes surprising insights into the quality of services and leads to a more quality-driven design and engineering of complex software architectures that use such services. Starting with a broad introduction to the field, this book guides readers step-by-step through the process of designing, implementing and executing a cloud service benchmark, as well as understanding and dealing with its results. It covers all aspects of cloud service benchmarking, i.e., both benchmarking the cloud and benchmarking in the cloud, at a basic level. The book is divided into five parts: Part I discusses what cloud benchmarking is, provides an overview of cloud services and their key properties, and describes the notion of a cloud system and cloud-service quality. It also addresses the benchmarking lifecycle and the motivations behind running benchmarks in particular phases of an application lifecycle. Part II then focuses on benchmark design by discussing key objectives (e.g., repeatability, fairness, or understandability) and defining metrics and measurement methods, and by giving advice on developing own measurement methods and metrics. Next, Part III explores benchmark execution and implementation challenges and objectives as well as aspects like runtime monitoring and result collection. Subsequently, Part IV addresses benchmark results, covering topics such as an abstract process for turning data into insights, data preprocessing, and basic data analysis methods. Lastly, Part V concludes the book with a summary, suggestions for further reading and pointers to benchmarking tools available on the Web. The book is intended for researchers and graduate students of computer science and related subjects looking for an introduction to benchmarking cloud services, but also for industry practitioners who are interested in evaluating the quality of cloud services or who want to assess key qualities of their own implementations through cloud-based experiments.