Domenico Talia - Böcker

Data Analysis in the Cloud introduces and discusses models, methods, techniques, and systems to analyze the large number of digital data sources available on the Internet using the computing and storage facilities of the cloud.

Coverage includes scalable data mining and knowledge discovery techniques together with cloud computing concepts, models, and systems. Specific sections focus on map-reduce and NoSQL models. The book also includes techniques for conducting high-performance distributed analysis of large data on clouds. Finally, the book examines research trends such as Big Data pervasive computing, data-intensive exascale computing, and massive social network analysis.

Introduces data analysis techniques and cloud computing concepts Describes cloud-based models and systems for Big Data analytics Provides examples of the state-of-the-art in cloud data analysis Explains how to develop large-scale data mining applications on clouds Outlines the main research trends in the area of scalable Big Data analysis

A new approach to distributed large-scale data mining, service-oriented knowledge discovery extracts useful knowledge from today’s often unmanageable volumes of data by exploiting data mining and machine learning distributed models and techniques in service-oriented infrastructures. Service-Oriented Distributed Knowledge Discovery presents techniques, algorithms, and systems based on the service-oriented paradigm. Through detailed descriptions of real software systems, it shows how the techniques, models, and architectures can be implemented.The book covers key areas in data mining and service-oriented computing. It presents the concepts and principles of distributed knowledge discovery and service-oriented data mining. The authors illustrate how to design services for data analytics, describe real systems for implementing distributed knowledge discovery applications, and explore mobile data mining models. They also discuss the future role of service-oriented knowledge discovery in ubiquitous discovery processes and large-scale data analytics.Highlighting the latest achievements in the field, the book gives many examples of the state of the art in service-oriented knowledge discovery. Both novices and more seasoned researchers will learn useful concepts related to distributed data mining and service-oriented data analysis. Developers will also gain insight on how to successfully use service-oriented knowledge discovery in databases (KDD) frameworks.

Data and knowledge play a key role in both current and future GRIDs. The issues concerning representation, discovery, and integration of data and knowledge in dynamic distributed environments can be addressed by exploiting features offered by GRID Technologies. Current research activities are leveraging the GRID for the provision of generic- and domain-specific solutions and services for data management and knowledge discovery.Knowledge and Data Management in GRIDs is the third volume of the CoreGRID series and brings together scientific contributions by researchers and scientists working on storage, data, and knowledge management in GRID and Peer-to-Peer systems. This volume presents the latest GRID solutions and research results in key areas of knowledge and data management such as distributed storage management, GRID databases, Semantic GRID and GRID-aware data mining.Knowledge and Data Management in GRIDs is designed for a professional audience, composed of researchers and practitioners in industry. This book is also suitable for graduate-level students in computer science.

Grid Middleware and Services: Challenges and Solutions is the eighth volume of the CoreGRID series. The CoreGrid Proceedings is the premiere European event on Grid Computing. This book aims to strengthen and advance scientific and technological excellence in the area of Grid Computing. The main focus in this volume is on Grid middleware and service level agreement.Grid middleware and Grid services are two pillars of grid computing systems and applications. This book includes high-level contributions by leading researchers in both areas and presents current solutions together with future challenges. This volume includes sections on knowledge and data management on grids, Grid resource management and scheduling, Grid information, resource and workflow monitoring services, and service level agreements.Grid Middleware and Services: Challenges and Solutions is designed for a professional audience, composed of researchers and practitioners in industry. This volume is also suitable for graduate-level students in computer science.

Grids are a crucial enabling technology for scientific and industrial development. Grid and Services Evolution, the 11th edited volume of the CoreGRID series, was based on The CoreGRID Middleware Workshop, held in Barcelona, Spain, June 5-6, 2008.Grid and Services Evolution provides a bridge between the application community and the developers of middleware services, especially in terms of parallel computing. This edited volume brings together a critical mass of well-established researchers worldwide, from forty-two institutions active in the fields of distributed systems and middleware, programming models, algorithms, tools and environments.Grid and Services Evolution is designed for a professional audience composed of researchers and practitioners within the Grid community industry. This volume is also suitable for advanced-level students in computer science.

A new approach to distributed large-scale data mining, service-oriented knowledge discovery extracts useful knowledge from today’s often unmanageable volumes of data by exploiting data mining and machine learning distributed models and techniques in service-oriented infrastructures. Service-Oriented Distributed Knowledge Discovery presents techniques, algorithms, and systems based on the service-oriented paradigm. Through detailed descriptions of real software systems, it shows how the techniques, models, and architectures can be implemented.The book covers key areas in data mining and service-oriented computing. It presents the concepts and principles of distributed knowledge discovery and service-oriented data mining. The authors illustrate how to design services for data analytics, describe real systems for implementing distributed knowledge discovery applications, and explore mobile data mining models. They also discuss the future role of service-oriented knowledge discovery in ubiquitous discovery processes and large-scale data analytics.Highlighting the latest achievements in the field, the book gives many examples of the state of the art in service-oriented knowledge discovery. Both novices and more seasoned researchers will learn useful concepts related to distributed data mining and service-oriented data analysis. Developers will also gain insight on how to successfully use service-oriented knowledge discovery in databases (KDD) frameworks.

The third volume of the CoreGRID series, Knowledge and Data Management in Grids presents the latest Grid solutions and research results in key areas such as distributed storage management, Grid databases, Semantic Grid and Grid-aware data mining.

Grid Middleware and Services: Challenges and Solutions is the eighth volume of the CoreGRID series. The CoreGrid Proceedings is the premiere European event on Grid Computing. This book aims to strengthen and advance scientific and technological excellence in the area of Grid Computing. The main focus in this volume is on Grid middleware and service level agreement.Grid middleware and Grid services are two pillars of grid computing systems and applications. This book includes high-level contributions by leading researchers in both areas and presents current solutions together with future challenges. This volume includes sections on knowledge and data management on grids, Grid resource management and scheduling, Grid information, resource and workflow monitoring services, and service level agreements.Grid Middleware and Services: Challenges and Solutions is designed for a professional audience, composed of researchers and practitioners in industry. This volume is also suitable for graduate-level students in computer science.

Grids are a crucial enabling technology for scientific and industrial development. Grid and Services Evolution, the 11th edited volume of the CoreGRID series, was based on The CoreGRID Middleware Workshop, held in Barcelona, Spain, June 5-6, 2008.Grid and Services Evolution provides a bridge between the application community and the developers of middleware services, especially in terms of parallel computing. This edited volume brings together a critical mass of well-established researchers worldwide, from forty-two institutions active in the fields of distributed systems and middleware, programming models, algorithms, tools and environments.Grid and Services Evolution is designed for a professional audience composed of researchers and practitioners within the Grid community industry. This volume is also suitable for advanced-level students in computer science.

Data and algorithms are changing our life. The awareness of importance and pervasiveness of the digital revolution is the primary element from which to start a path of knowledge to grasp what is happening in the world of big data and digital innovation and to understand these impacts on our minds and relationships between people, traceability and the computability of behavior of individuals and social organizations.This book analyses contemporary and future issues related to big data, algorithms, data analysis, artificial intelligence and the internet. It introduces and discusses relationships between digital technologies and power, the role of the pervasive algorithms in our life and the risk of technological alienation, the relationships between the use of big data, the privacy of citizens and the exercise of democracy, the techniques of artificial intelligence and their impact on the labor world, the Industry 4.0 at the time of the Internet of Things, social media, open data and public innovation.Each chapter raises a set of questions and answers to help the reader to know the key issues in the enormous maze that the tools of info-communication have built around us.

Data and algorithms are changing our life. The awareness of importance and pervasiveness of the digital revolution is the primary element from which to start a path of knowledge to grasp what is happening in the world of big data and digital innovation and to understand these impacts on our minds and relationships between people, traceability and the computability of behavior of individuals and social organizations.This book analyses contemporary and future issues related to big data, algorithms, data analysis, artificial intelligence and the internet. It introduces and discusses relationships between digital technologies and power, the role of the pervasive algorithms in our life and the risk of technological alienation, the relationships between the use of big data, the privacy of citizens and the exercise of democracy, the techniques of artificial intelligence and their impact on the labor world, the Industry 4.0 at the time of the Internet of Things, social media, open data and public innovation.Each chapter raises a set of questions and answers to help the reader to know the key issues in the enormous maze that the tools of info-communication have built around us.

In the age of the Internet of Things and social media platforms, huge amounts of digital data are generated by and collected from many sources, including sensors, mobile devices, wearable trackers and security cameras. These data, commonly referred to as big data, are challenging current storage, processing and analysis capabilities. New models, languages, systems and algorithms continue to be developed to effectively collect, store, analyze and learn from big data.Programming Big Data Applications introduces and discusses models, programming frameworks and algorithms to process and analyze large amounts of data. In particular, the book provides an in-depth description of the properties and mechanisms of the main programming paradigms for big data analysis, including MapReduce, workflow, BSP, message passing, and SQL-like. Through programming examples it also describes the most used frameworks for big data analysis like Hadoop, Spark, MPI, Hive and Storm. Each of the different systems is discussed and compared, highlighting their main features, their diffusion (both within their community of developers and among users), and their main advantages and disadvantages in implementing big data analysis applications.

This book constitutes the refereed post-conference proceedings of the First International Conference on Pervasive Knowledge and Collective Intelligence on Web and Social Media, PerSOM 2022, which was held in Messina, Italy, in November 2022.The 9 full papers were carefully reviewed and selected from 35 submissions and present findings of research from the fields of pervasive computing, web, and social media to promote ideas and practices about pervasive knowledge and collective intelligence in this fields. The conference targeted a wide variety of topics including new perspectives in social theories, complex networks, data science, knowledge management, web and social media.

This two volume set LNCS 8285 and 8286 constitutes the proceedings of the 13th International Conference on Algorithms and Architectures for Parallel Processing, ICA3PP 2013, held in Vietri sul Mare, Italy in December 2013. The first volume contains 10 distinguished and 31 regular papers selected from 90 submissions and covering topics such as big data, multi-core programming and software tools, distributed scheduling and load balancing, high-performance scientific computing, parallel algorithms, parallel architectures, scalable and distributed databases, dependability in distributed and parallel systems, wireless and mobile computing. The second volume consists of four sections including 35 papers from one symposium and three workshops held in conjunction with ICA3PP 2013 main conference. These are 13 papers from the 2013 International Symposium on Advances of Distributed and Parallel Computing (ADPC 2013), 5 papers of the International Workshop on Big Data Computing (BDC 2013), 10 papers of the International Workshop on Trusted Information in Big Data (TIBiDa 2013) as well as 7 papers belonging to Workshop on Cloud-assisted Smart Cyber-Physical Systems (C-Smart CPS 2013).

Euro-Par is an annual series of international conferences dedicated to the p- motion and advancementof allaspects of parallelcomputing. The major themes can be divided into four broad categories: theory, high-performance, cluster and grid,distributedandmobilecomputing.Thesecategoriescomprise14topicsthat focus on particular issues. The objective of Euro-Paris to provide a forum within which to promote the development of parallel computing both as an industrial technique and an a- demic discipline, extending the frontier of both the state of the art and the state of practice. The main audience for and participants in Euro-Par are researchers inacademicdepartments,governmentlaboratories,andindustrialorganizations. Euro-Par2010 was the 16th conference in the Euro-Parseries, and was or- nizedbythe Institute forHigh-PerformanceComputingandNetworking(ICAR) of the Italian National Research Council (CNR), in Ischia, Italy. Previous Euro- ParconferencestookplaceinStockholm,Lyon,Passau,Southampton,Toulouse, Munich, Manchester, Padderborn, Klagenfurt, Pisa, Lisbon, Dresden, Rennes, Las Palmas, and Delft. Next year the conference will take place in Bordeaux, France.More information on the Euro-Par conference series and organization is available on the wesite http://www.europar.org. As mentioned before, the conference was organized in 14 topics. The paper review process for each topic was managed and supervised by a committee of at least four persons: a Global Chair, a Local Chair, and two members. Some speci?c topics with a high number of submissions were managed by a larger committeewithmoremembers.The?naldecisionsontheacceptanceorrejection ofthesubmitted papersweremadein ameeting ofthe ConferenceCo-chairsand Local Chairs of the topics.

Euro-Par is an annual series of international conferences dedicated to the p- motion and advancementof allaspects of parallelcomputing. The major themes can be divided into four broad categories: theory, high-performance, cluster and grid,distributedandmobilecomputing.Thesecategoriescomprise14topicsthat focus on particular issues. The objective of Euro-Paris to provide a forum within which to promote the development of parallel computing both as an industrial technique and an a- demic discipline, extending the frontier of both the state of the art and the state of practice. The main audience for and participants in Euro-Par are researchers inacademicdepartments,governmentlaboratories,andindustrialorganizations. Euro-Par2010 was the 16th conference in the Euro-Parseries, and was or- nizedbythe Institute forHigh-PerformanceComputingandNetworking(ICAR) of the Italian National Research Council (CNR), in Ischia, Italy. Previous Euro- ParconferencestookplaceinStockholm,Lyon,Passau,Southampton,Toulouse, Munich, Manchester, Padderborn, Klagenfurt, Pisa, Lisbon, Dresden, Rennes, Las Palmas, and Delft. Next year the conference will take place in Bordeaux, France.More information on the Euro-Par conference series and organization is available on the wesite http://www.europar.org. As mentioned before, the conference was organized in 14 topics. The paper review process for each topic was managed and supervised by a committee of at least four persons: a Global Chair, a Local Chair, and two members. Some speci?c topics with a high number of submissions were managed by a larger committeewithmoremembers.The?naldecisionsontheacceptanceorrejection ofthesubmitted papersweremadein ameeting ofthe ConferenceCo-chairsand Local Chairs of the topics.

This book introduces and provides an analysis of the basic concepts of algorithms, data, and computation and discusses the role of algorithms in ruling and shaping our world. It provides a clear understanding of the power and impact on humanity of the pervasive use of algorithms.From Algorithms to Thinking Machines combines a layman's approach with a well-founded scientific description to discuss both principles and applications of algorithms, Big Data, and machine intelligence. The book provides a clear and deep description of algorithms, software systems, data-driven applications, machine learning, and data science concepts, as well as the evolution and impact of artificial intelligence.After introducing computing concepts, the book examines the relationships between algorithms and human work, discussing how jobs are being affected and how computers and software programs are influencing human life and the labor sphere. Topics such as value alignment, collective intelligence, Big Data impact, automatic decision methods, social control, and political uses of algorithms are illustrated and discussed at length without excessive technical detail. Issues related to how corporations, governments, and autocratic regimes are exploiting algorithms and machine intelligence methods to influence people, laws, and markets are extensively addressed. Ethics principles in software programming and human value insertion into artificial intelligence algorithms are also discussed.