Athman Bouguettaya

In practice, the design and architecture of a cloud varies among cloud providers. We present a generic evaluation framework for the performance, availability and reliability characteristics of various cloud platforms. We describe a generic benchmark architecture for cloud databases, specifically NoSQL database as a service. It measures the performance of replication delay and monetary cost. Service Level Agreements (SLA) represent the contract which captures the agreed upon guarantees between a service provider and its customers. The specifications of existing service level agreements (SLA) for cloud services are not designed to flexibly handle even relatively straightforward performance and technical requirements of consumer applications. We present a novel approach for SLA-based management of cloud-hosted databases from the consumer perspective and an end-to-end framework for consumer-centric SLA management of cloud-hosted databases. The framework facilitates adaptive and dynamic provisioning of the database tier of the software applications based on application-defined policies for satisfying their own SLA performance requirements, avoiding the cost of any SLA violation and controlling the monetary cost of the allocated computing resources. In this framework, the SLA of the consumer applications are declaratively defined in terms of goals which are subjected to a number of constraints that are specific to the application requirements. The framework continuously monitors the application-defined SLA and automatically triggers the execution of necessary corrective actions (scaling out/in the database tier) when required. The framework is database platform-agnostic, uses virtualization-based database replication mechanisms and requires zero source code changes of the cloud-hosted software applications.

In practice, the design and architecture of a cloud varies among cloud providers. We present a generic evaluation framework for the performance, availability and reliability characteristics of various cloud platforms. We describe a generic benchmark architecture for cloud databases, specifically NoSQL database as a service. It measures the performance of replication delay and monetary cost. Service Level Agreements (SLA) represent the contract which captures the agreed upon guarantees between a service provider and its customers. The specifications of existing service level agreements (SLA) for cloud services are not designed to flexibly handle even relatively straightforward performance and technical requirements of consumer applications. We present a novel approach for SLA-based management of cloud-hosted databases from the consumer perspective and an end-to-end framework for consumer-centric SLA management of cloud-hosted databases. The framework facilitates adaptive and dynamic provisioning of the database tier of the software applications based on application-defined policies for satisfying their own SLA performance requirements, avoiding the cost of any SLA violation and controlling the monetary cost of the allocated computing resources. In this framework, the SLA of the consumer applications are declaratively defined in terms of goals which are subjected to a number of constraints that are specific to the application requirements. The framework continuously monitors the application-defined SLA and automatically triggers the execution of necessary corrective actions (scaling out/in the database tier) when required. The framework is database platform-agnostic, uses virtualization-based database replication mechanisms and requires zero source code changes of the cloud-hosted software applications.

The authors introduce both the quantitative and qualitative economic models as optimization tools for the selection of long-term cloud service requests. The economic models fit almost intuitively in the way business is usually done and maximize the profit of a cloud provider for a long-term period. The authors propose a new multivariate Hidden Markov and Autoregressive Integrated Moving Average (HMM-ARIMA) model to predict various patterns of runtime resource utilization. A heuristic-based Integer Linear Programming (ILP) optimization approach is developed to maximize the runtime resource utilization. It deploys a Dynamic Bayesian Network (DBN) to model the dynamic pricing and long-term operating cost. A new Hybrid Adaptive Genetic Algorithm (HAGA) is proposed that optimizes a non-linear profit function periodically to address the stochastic arrival of requests. Next, the authors explore the Temporal Conditional Preference Network (TempCP-Net) as the qualitative economic model to represent the high-level IaaS business strategies. The temporal qualitative preferences are indexed in a multidimensional k-d tree to efficiently compute the preference ranking at runtime. A three-dimensional Q-learning approach is developed to find an optimal qualitative composition using statistical analysis on historical request patterns. Finally, the authors propose a new multivariate approach to predict future Quality of Service (QoS) performances of peer service providers to efficiently configure a TempCP-Net. It discusses the experimental results and evaluates the efficiency of the proposed composition framework using Google Cluster data, real-world QoS data, and synthetic data. It also explores the significance of the proposed approach in creating an economically viable and stable cloud market. This book can be utilized as a useful reference to anyone who is interested in theory, practice, and application of economic models in cloud computing. This book will be an invaluable guide for small and medium entrepreneurs who have invested or plan to invest in cloud infrastructures and services. Overall, this book is suitable for a wide audience that includes students, researchers, and practitioners studying or working in service-oriented computing and cloud computing.

This book develops a crowdsourced sensor-cloud service composition framework taking into account spatio-temporal aspects. This book also unfolds new horizons to service-oriented computing towards the direction of crowdsourced sensor data based applications, in the broader context of Internet of Things (IoT). It is a massive challenge for the IoT research field how to effectively and efficiently capture, manage and deliver sensed data as user-desired services. The outcome of this research will contribute to solving this very important question, by designing a novel service framework and a set of unique service selection and composition frameworks. Delivering a novel service framework to manage crowdsourced sensor data provides high-level abstraction (i.e., sensor-cloud service) to model crowdsourced sensor data from functional and non-functional perspectives, seamlessly turning the raw data into “ready to go” services. A creative indexing model is developed to capture and manage the spatio-temporal dynamism of crowdsourced service providers. Delivering novel frameworks to compose crowdsourced sensor-cloud services is vital. These frameworks focuses on spatio-temporal composition of crowdsourced sensor-cloud services, which is a new territory for existing service oriented computing research. A creative failure-proof model is also designed to prevent composition failure caused by fluctuating QoS. Delivering an incentive model to drive the coverage of crowdsourced service providers is also vital. A new spatio-temporal incentive model targets changing coverage of the crowdsourced providers to achieve demanded coverage of crowdsourced sensor-cloud services within a region. The outcome of this research is expected to potentially create a sensor services crowdsourcing market and new commercial opportunities focusing on crowdsourced data based applications. The crowdsourced community based approach adds significant value to journey planning and map services thus creating a competitive edge for a technologically-minded companies incentivizing new start-ups, thus enabling higher market innovation. This book primarily targets researchers and practitioners, who conduct research work in service oriented computing, Internet of Things (IoT), smart city and spatio-temporal travel planning, as well as advanced-level students studying this field. Small and Medium Entrepreneurs, who invest in crowdsourced IoT services and journey planning infrastructures, will also want to purchase this book.

This book develops a crowdsourced sensor-cloud service composition framework taking into account spatio-temporal aspects. This book also unfolds new horizons to service-oriented computing towards the direction of crowdsourced sensor data based applications, in the broader context of Internet of Things (IoT). It is a massive challenge for the IoT research field how to effectively and efficiently capture, manage and deliver sensed data as user-desired services. The outcome of this research will contribute to solving this very important question, by designing a novel service framework and a set of unique service selection and composition frameworks. Delivering a novel service framework to manage crowdsourced sensor data provides high-level abstraction (i.e., sensor-cloud service) to model crowdsourced sensor data from functional and non-functional perspectives, seamlessly turning the raw data into “ready to go” services. A creative indexing model is developed to capture and manage the spatio-temporal dynamism of crowdsourced service providers. Delivering novel frameworks to compose crowdsourced sensor-cloud services is vital. These frameworks focuses on spatio-temporal composition of crowdsourced sensor-cloud services, which is a new territory for existing service oriented computing research. A creative failure-proof model is also designed to prevent composition failure caused by fluctuating QoS. Delivering an incentive model to drive the coverage of crowdsourced service providers is also vital. A new spatio-temporal incentive model targets changing coverage of the crowdsourced providers to achieve demanded coverage of crowdsourced sensor-cloud services within a region. The outcome of this research is expected to potentially create a sensor services crowdsourcing market and new commercial opportunities focusing on crowdsourced data based applications. The crowdsourced community based approach adds significant value to journey planning and map services thus creating a competitive edge for a technologically-minded companies incentivizing new start-ups, thus enabling higher market innovation. This book primarily targets researchers and practitioners, who conduct research work in service oriented computing, Internet of Things (IoT), smart city and spatio-temporal travel planning, as well as advanced-level students studying this field. Small and Medium Entrepreneurs, who invest in crowdsourced IoT services and journey planning infrastructures, will also want to purchase this book.

The authors introduce both the quantitative and qualitative economic models as optimization tools for the selection of long-term cloud service requests. The economic models fit almost intuitively in the way business is usually done and maximize the profit of a cloud provider for a long-term period. The authors propose a new multivariate Hidden Markov and Autoregressive Integrated Moving Average (HMM-ARIMA) model to predict various patterns of runtime resource utilization. A heuristic-based Integer Linear Programming (ILP) optimization approach is developed to maximize the runtime resource utilization. It deploys a Dynamic Bayesian Network (DBN) to model the dynamic pricing and long-term operating cost. A new Hybrid Adaptive Genetic Algorithm (HAGA) is proposed that optimizes a non-linear profit function periodically to address the stochastic arrival of requests. Next, the authors explore the Temporal Conditional Preference Network (TempCP-Net) as the qualitative economic model to represent the high-level IaaS business strategies. The temporal qualitative preferences are indexed in a multidimensional k-d tree to efficiently compute the preference ranking at runtime. A three-dimensional Q-learning approach is developed to find an optimal qualitative composition using statistical analysis on historical request patterns. Finally, the authors propose a new multivariate approach to predict future Quality of Service (QoS) performances of peer service providers to efficiently configure a TempCP-Net. It discusses the experimental results and evaluates the efficiency of the proposed composition framework using Google Cluster data, real-world QoS data, and synthetic data. It also explores the significance of the proposed approach in creating an economically viable and stable cloud market. This book can be utilized as a useful reference to anyone who is interested in theory, practice, and application of economic models in cloud computing. This book will be an invaluable guide for small and medium entrepreneurs who have invested or plan to invest in cloud infrastructures and services. Overall, this book is suitable for a wide audience that includes students, researchers, and practitioners studying or working in service-oriented computing and cloud computing.

This book describes the design and implementation of Cloud Armor, a novel approach for credibility-based trust management and automatic discovery of cloud services in distributed and highly dynamic environments. This book also helps cloud users to understand the difficulties of establishing trust in cloud computing and the best criteria for selecting a service cloud. The techniques have been validated by a prototype system implementation and experimental studies using a collection of real world trust feedbacks on cloud services. The authors present the design and implementation of a novel protocol that preserves the consumers’ privacy, an adaptive and robust credibility model, a scalable availability model that relies on a decentralized architecture, and a cloud service crawler engine for automatic cloud services discovery. This book also analyzes results from a performance study on a number of open research issues for trust management in cloud environments including distribution of providers, geographic location and languages. These open research issues illustrate both an overview of the current state of cloud computing and potential future directions for the field. Trust Management in Cloud Services contains both theoretical and applied computing research, making it an ideal reference or secondary text book to both academic and industry professionals interested in cloud services. Advanced-level students in computer science and electrical engineering will also find the content valuable.

This book describes the design and implementation of Cloud Armor, a novel approach for credibility-based trust management and automatic discovery of cloud services in distributed and highly dynamic environments. This book also helps cloud users to understand the difficulties of establishing trust in cloud computing and the best criteria for selecting a service cloud. The techniques have been validated by a prototype system implementation and experimental studies using a collection of real world trust feedbacks on cloud services. The authors present the design and implementation of a novel protocol that preserves the consumers’ privacy, an adaptive and robust credibility model, a scalable availability model that relies on a decentralized architecture, and a cloud service crawler engine for automatic cloud services discovery. This book also analyzes results from a performance study on a number of open research issues for trust management in cloud environments including distribution of providers, geographic location and languages. These open research issues illustrate both an overview of the current state of cloud computing and potential future directions for the field. Trust Management in Cloud Services contains both theoretical and applied computing research, making it an ideal reference or secondary text book to both academic and industry professionals interested in cloud services. Advanced-level students in computer science and electrical engineering will also find the content valuable.

Foundations for Efficient Web Service Selection describes the foundational framework for efficient Web service selection. It lays out a theoretical underpinning for the design of models and algorithms for searching and optimizing access to Web services. Excerpts from Prof. Fabio Casati’s foreword: " This excellent book looks at the search problem from a broader perspective. Instead of narrowing down on a specific aspect or subproblem of service search, it dissects and analyzes the fundamental problems in search and presents concrete, applicable solutions as well as the theoretical foundations behind them…One aspect I found particularly significant in the book is the mind shift it generates from thinking about service modeling for the sake of supporting deployment or invocation to modeling for supporting search. This design for search approach is exactly what we do when we design databases because search is what we worry about in that case, and there is no reason why this shouldn’t be the case for services if we want services to be searchable with a similar effectiveness."

Web services and service oriented environments are key enablers for the migration of entertainment, business, sociability, science and health-care from the physical world to the virtual world. The result of this on-going migration is a new place very much different from the physical world, one where interconnected services interact with human users, sensors and embedded devices. Yet for this vision to become reality, trust needs to be addressed as members of the global e-society r- ularly today deal with the question whether they can trust other, unknown parties. Trust is a vital component of internet-based interactions and service-oriented en- ronment, but all too often it is assumed to be an implicit property that exists in the background rather than being an explicit property that is well-de ned and quant- able. While providing trust is challenging in existing computing systems, providing trust in service oriented environments is much more complex due to the dynamic and adaptable nature of these environment which are often large scale and across domains. To date the problem of trust for service oriented environments has been largely unexplored. This book represents the rst comprehensivecoverageof the principles,methods and systems for trust management and evaluation in service oriented environments.

The new computing environment enabled by advances in service oriented arc- tectures, mashups, and cloud computing will consist of service spaces comprising data, applications, infrastructure resources distributed over the Web. This envir- ment embraces a holistic paradigm in which users, services, and resources establish on-demand interactions, possibly in real-time, to realise useful experiences. Such interactions obtain relevant services that are targeted to the time and place of the user requesting the service and to the device used to access it. The bene?t of such environment originates from the added value generated by the possible interactions in a large scale rather than by the capabilities of its individual components se- rately. This offers tremendous automation opportunities in a variety of application domains including execution of forecasting, of?ce tasks, travel support, intelligent information gathering and analysis, environment monitoring, healthcare, e-business, community based systems, e-science and e-government. A key feature of this environment is the ability to dynamically compose services to realise user tasks. While recent advances in service discovery, composition and Semantic Web technologies contribute necessary ?rst steps to facilitate this task, the bene?ts of composition are still limited to take advantages of large-scale ubiq- tous environments. The main stream composition techniques and technologies rely on human understanding and manual programming to compose and aggregate s- vices. Recent advances improve composition by leveraging search technologies and ?ow-based composition languages as in mashups and process-centric service c- position.

Service Composition for the Semantic Web presents an in-depth analysis of aspects related to semantic-enabled Web service modeling and composition. It also covers challenges and solutions to composing Web services on the semantic Web, and proposing a semantic framework for organizing and describing Web services. Service Composition for the Semantic Web describes composability and matching models to check whether semantic Web services can be combined together to avoid unexpected failures at run time, and a set of algorithms that automatically generate detailed descriptions of composite services from high-level specifications of composition requests. The book includes case studies in the areas of digital government and bioinformatics.

Change Management for Semantic Web Services provides a thorough analysis of change management in the lifecycle of services for databases and workflows, including changes that occur at the individual service level or at the aggregate composed service level. This book describes taxonomy of changes that are expected in semantic service oriented environments. The process of change management consists of detecting, propagating, and reacting to changes. Change Management for Semantic Web Services is one of the first books that discuss the development of a theoretical foundation for managing changes in atomic and long-term composed services. This book also proposes a formal model and a change language to provide sufficient semantics for change management; it devises an automatic process to react to, verify, and optimize changes. Case studies and examples are presented in the last section of this book.

Semantic Web Services for Web Databases introduces an end-to-end framework for querying Web databases using novel Web service querying techniques. This includes a detailed framework for the query infrastructure for Web databases and services. Case studies are covered in the last section of this book. Semantic Web Services For Web Databases is designed for practitioners and researchers focused on service-oriented computing and Web databases.

Information systems are the backbone of many of today's computerized applications. Distributed databases and the infrastructure needed to support them have been well studied. However, this book is the first to address distributed database interoperability by examining the successes and failures, various approaches, infrastructures, and trends of the field. A gap exists in the way that these systems have been investigated by real practitioners. This gap is more pronounced than usual, partly because of the way businesses operate, the systems they have, and the difficulties created by systems' autonomy and heterogeneity. Telecommunications firms, for example, must deal with an increased demand for automation while at the same time continuing to function at their current level. While academics are focusing on investigating differences between distributed databases, federated databases, heterogeneous databases, and, more generally, among loosely connected and tightly coupled systems, those who have to deal with real problems right away know that the only relevant research is the one that will ensure that their system works to produce reasonably correct results. Interconnecting Heterogeneous Information Systems covers the underlying principles and infrastructures needed to realize truly global information systems. The book discusses technologies related to middleware, the Web, workflows, transactions, and data warehousing. It also overviews architectures with a discussion of critical issues. The book gives an overview of systems that can be viewed as learning platforms. While these systems do not translate to successful commercial realities, they push the envelope in terms of research. Successful commercial systems have benefited from the experiments conducted in these prototypes. The book includes two case studies based on the authors' own work. Interconnecting Heterogeneous Information Systems issuitable as a textbook for a graduate-level course on Interconnecting Heterogeneous Information Systems, as well as a secondary text for a graduate-level course on database or information systems, and as a reference for researchers and practitioners in industry.

Semantic Web Services for Web Databases introduces an end-to-end framework for querying Web databases using novel Web service querying techniques. This includes a detailed framework for the query infrastructure for Web databases and services. Case studies are covered in the last section of this book. Semantic Web Services For Web Databases is designed for practitioners and researchers focused on service-oriented computing and Web databases.

Change Management for Semantic Web Services provides a thorough analysis of change management in the lifecycle of services for databases and workflows, including changes that occur at the individual service level or at the aggregate composed service level. This book describes taxonomy of changes that are expected in semantic service oriented environments. The process of change management consists of detecting, propagating, and reacting to changes. Change Management for Semantic Web Services is one of the first books that discuss the development of a theoretical foundation for managing changes in atomic and long-term composed services. This book also proposes a formal model and a change language to provide sufficient semantics for change management; it devises an automatic process to react to, verify, and optimize changes. Case studies and examples are presented in the last section of this book.

Service Composition for the Semantic Web presents an in-depth analysis of aspects related to semantic-enabled Web service modeling and composition. It also covers challenges and solutions to composing Web services on the semantic Web, and proposing a semantic framework for organizing and describing Web services. Service Composition for the Semantic Web describes composability and matching models to check whether semantic Web services can be combined together to avoid unexpected failures at run time, and a set of algorithms that automatically generate detailed descriptions of composite services from high-level specifications of composition requests. The book includes case studies in the areas of digital government and bioinformatics.

Access to Mobile Services focuses on methods for accessing broadcast based M-services from multiple wireless channels. This book presents a novel infrastructure that provides a multi-channel broadcast framework for mobile users to effectively discover and access composite M-services. Multi-channel algorithms are proposed for efficiently accessing composite services. Access to Mobile Services provides an in-depth survey of wireless data access and motivates the need to treat mobile services differently. A wireless adaptation of Service Oriented Architecture (SOA) is also covered. Designed for researchers and practitioners who work in the general area of mobile services, this book is also suitable for advanced-level students in computer science. Forewords by: Michael P. Papazoglou, Tilburg University, The NetherlandsFabio Casati, University of Trento, Italy

The new computing environment enabled by advances in service oriented arc- tectures, mashups, and cloud computing will consist of service spaces comprising data, applications, infrastructure resources distributed over the Web. This envir- ment embraces a holistic paradigm in which users, services, and resources establish on-demand interactions, possibly in real-time, to realise useful experiences. Such interactions obtain relevant services that are targeted to the time and place of the user requesting the service and to the device used to access it. The bene?t of such environment originates from the added value generated by the possible interactions in a large scale rather than by the capabilities of its individual components se- rately. This offers tremendous automation opportunities in a variety of application domains including execution of forecasting, of?ce tasks, travel support, intelligent information gathering and analysis, environment monitoring, healthcare, e-business, community based systems, e-science and e-government. A key feature of this environment is the ability to dynamically compose services to realise user tasks. While recent advances in service discovery, composition and Semantic Web technologies contribute necessary ?rst steps to facilitate this task, the bene?ts of composition are still limited to take advantages of large-scale ubiq- tous environments. The main stream composition techniques and technologies rely on human understanding and manual programming to compose and aggregate s- vices. Recent advances improve composition by leveraging search technologies and ?ow-based composition languages as in mashups and process-centric service c- position.