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This book constitutes the thoroughly refereed post-conference proceedings of the 8th TPC Technology Conference, on Performance Evaluation and Benchmarking, TPCTC 2016, held in conjunction with the 41st International Conference on Very Large Databases (VLDB 2016) in New Delhi, India, in September 2016. The 9 papers presented were carefully reviewed and selected from 20 submissions. They reflect the rapid pace at which industry experts and researchers develop innovative techniques for evaluation, measurement and characterization of complex systems.
This book constitutes the thoroughly refereed post-conference proceedings of the 7th TPC Technology Conference on Performance Evaluation and Benchmarking, TPSTC 2015, held in conjunction with the 40th International Conference on Very Large Databases (VLDB 2015) in Kohala Coast, Hawaii, USA, in August/September 2015. The 8 papers presented together with 1 keynote, and 1 vision paper were carefully reviewed and selected from 24 submissions. Many buyers use TPC benchmark results as points of comparison when purchasing new computing systems. The information technology landscape is evolving at a rapid pace, challenging industry experts and researchers to develop innovative techniques for evaluation, measurement and characterization of complex systems. The TPC remains committed to developing new benchmark standards to keep pace, and one vehicle for achieving this objective is the sponsorship of the Technology Conference on Performance Evaluation and Benchmarking (TPCTC).
This book constitutes the thoroughly refereed post-conference proceedings of the 8th TPC Technology Conference, on Performance Evaluation and Benchmarking, TPCTC 2017, held in conjunction with the43rd International Conference on Very Large Databases (VLDB 2017) in August/September 2017. The 12 papers presented were carefully reviewed and selected from numeroussubmissions. The TPC remains committed to developing new benchmark standards to keep pace with these rapid changes in technology.
This volume LNCS 12925 constitutes the papers of the 23rd International Conference on Big Data Analytics and Knowledge Discovery, held in September 2021. Due to COVID-19 pandemic it was held virtually. The 12 full papers presented together with 15 short papers in this volume were carefully reviewed and selected from a total of 71 submissions. The papers reflect a wide range of topics in the field of data integration, data warehousing, data analytics, and recently big data analytics, in a broad sense. The main objectives of this event are to explore, disseminate, and exchange knowledge in these fields.
This book includes 46 scientific papers presented at the conference and reflecting the latest research in the fields of data mining, machine learning and decision-making. The international scientific conference “Intellectual Systems of Decision-Making and Problems of Computational Intelligence” was held in the Kherson region, Ukraine, from May 25 to 29, 2020. The papers are divided into three sections: “Analysis and Modeling of Complex Systems and Processes,” “Theoretical and Applied Aspects of Decision-Making Systems” and “Computational Intelligence and Inductive Modeling.” The book will be of interest to scientists and developers specialized in the fields of data mining, machine learning and decision-making systems.
This book gathers the proceedings of the 2017 DepCoS-RELCOMEX, an annual conference series that has been organized by the Department of Computer Engineering at the Faculty of Electronics, Wrocław University of Science and Technology, since 2006. Its mission is to continue the heritage of the other two cycles of events – the RELCOMEX conferences (1977–89) and Microcomputer Schools (1985–95) – so this year we can celebrate the 40th anniversary of its origins. In contrast to those preceding series, which were focused on conventional reliability analysis, the goal of DepCoS is to promote a more comprehensive approach to system performability, which is now commonly called dependability. This innovative research area provides answers to the latest challenges in reliability evaluation for contemporary complex systems. Its novelty is based on a multi-disciplinary approach to system theory, technology and maintenance of systems operating in real environments. Dependability analyses concentrate on the efficient completion of tasks, services and jobs by a system considered as a combination of technical, information and human assets, in contrast to “classical” reliability, which is generally limited to the analysis of technical resources and associated components and structures. The selection of papers for this volume illustrates the diversity of topics that need to be considered, from mathematical models and design methodologies through software engineering and data security issues, to practical engineering problems in technical systems. In addition, this edition of the conference hosted the 7th CrISS-DESSERT Workshop, which was devoted to the analysis and assurance of safety and cyber security in critical infrastructure and computer systems.
This innovative new textbook, co-authored by an established academic and a leading practitioner, is the first to bring together issues of cloud computing, business intelligence and big data analytics in order to explore how organisations use cloud technology to analyse data and make decisions. In addition to offering an up-to-date exploration of key issues relating to data privacy and ethics, information governance, and the future of analytics, the text describes the options available in deploying analytic solutions to the cloud and draws on real-world, international examples from companies such as Rolls Royce, Lego, Volkswagen and Samsung. Combining academic and practitioner perspectives that are crucial to the understanding of this growing field, Business Analytics acts an ideal core text for undergraduate, postgraduate and MBA modules on Big Data, Business and Data Analytics, and Business Intelligence, as well as functioning as a supplementary text for modules in Marketing Analytics. The book is also an invaluable resource for practitioners and will quickly enable the next generation of 'Information Builders' within organisations to understand innovative cloud based-analytic solutions.
This book serves as both a textbook and handbook on the benchmarking of systems and components used as building blocks of modern information and communication technology applications. It provides theoretical and practical foundations as well as an in-depth exploration of modern benchmarks and benchmark development. The book is divided into two parts: foundations and applications. The first part introduces the foundations of benchmarking as a discipline, covering the three fundamental elements of each benchmarking approach: metrics, workloads, and measurement methodology. The second part focuses on different application areas, presenting contributions in specific fields of benchmark development. These contributions address the unique challenges that arise in the conception and development of benchmarks for specific systems or subsystems, and demonstrate how the foundations and concepts in the first part of the book are being used in existing benchmarks. Further, the book presents a number of concrete applications and case studies based on input from leading benchmark developers from consortia such as the Standard Performance Evaluation Corporation (SPEC) and the Transaction Processing Performance Council (TPC). Providing both practical and theoretical foundations, as well as a detailed discussion of modern benchmarks and their development, the book is intended as a handbook for professionals and researchers working in areas related to benchmarking. It offers an up-to-date point of reference for existing work as well as latest results, research challenges, and future research directions. It also can be used as a textbook for graduate and postgraduate students studying any of the many subjects related to benchmarking. While readers are assumed to be familiar with the principles and practices of computer science, as well as software and systems engineering, no specific expertise in any subfield of these disciplines is required.
A comprehensive guide to Fog and Edge applications, architectures, and technologies Recent years have seen the explosive growth of the Internet of Things (IoT): the internet-connected network of devices that includes everything from personal electronics and home appliances to automobiles and industrial machinery. Responding to the ever-increasing bandwidth demands of the IoT, Fog and Edge computing concepts have developed to collect, analyze, and process data more efficiently than traditional cloud architecture. Fog and Edge Computing: Principles and Paradigms provides a comprehensive overview of the state-of-the-art applications and architectures driving this dynamic field of computing while highlighting potential research directions and emerging technologies. Exploring topics such as developing scalable architectures, moving from closed systems to open systems, and ethical issues rising from data sensing, this timely book addresses both the challenges and opportunities that Fog and Edge computing presents. Contributions from leading IoT experts discuss federating Edge resources, middleware design issues, data management and predictive analysis, smart transportation and surveillance applications, and more. A coordinated and integrated presentation of topics helps readers gain thorough knowledge of the foundations, applications, and issues that are central to Fog and Edge computing. This valuable resource: Provides insights on transitioning from current Cloud-centric and 4G/5G wireless environments to Fog Computing Examines methods to optimize virtualized, pooled, and shared resources Identifies potential technical challenges and offers suggestions for possible solutions Discusses major components of Fog and Edge computing architectures such as middleware, interaction protocols, and autonomic management Includes access to a website portal for advanced online resources Fog and Edge Computing: Principles and Paradigms is an essential source of up-to-date information for systems architects, developers, researchers, and advanced undergraduate and graduate students in fields of computer science and engineering.
Big data has presented a number of opportunities across industries. With these opportunities come a number of challenges associated with handling, analyzing, and storing large data sets. One solution to this challenge is cloud computing, which supports a massive storage and computation facility in order to accommodate big data processing. Managing and Processing Big Data in Cloud Computing explores the challenges of supporting big data processing and cloud-based platforms as a proposed solution. Emphasizing a number of crucial topics such as data analytics, wireless networks, mobile clouds, and machine learning, this publication meets the research needs of data analysts, IT professionals, researchers, graduate students, and educators in the areas of data science, computer programming, and IT development.