Benchmarking, Consistency, Distributed Database Management Systems, Distributed Systems, Eventual Consistency


Book Description

Cloud storage services and NoSQL systems typically offer only "Eventual Consistency", a rather weak guarantee covering a broad range of potential data consistency behavior. The degree of actual (in-)consistency, however, is unknown. This work presents novel solutions for determining the degree of (in-)consistency via simulation and benchmarking, as well as the necessary means to resolve inconsistencies leveraging this information.




Fast and Scalable Cloud Data Management


Book Description

The unprecedented scale at which data is both produced and consumed today has generated a large demand for scalable data management solutions facilitating fast access from all over the world. As one consequence, a plethora of non-relational, distributed NoSQL database systems have risen in recent years and today’s data management system landscape has thus become somewhat hard to overlook. As another consequence, complex polyglot designs and elaborate schemes for data distribution and delivery have become the norm for building applications that connect users and organizations across the globe – but choosing the right combination of systems for a given use case has become increasingly difficult as well. To help practitioners stay on top of that challenge, this book presents a comprehensive overview and classification of the current system landscape in cloud data management as well as a survey of the state-of-the-art approaches for efficient data distribution and delivery to end-user devices. The topics covered thus range from NoSQL storage systems and polyglot architectures (backend) over distributed transactions and Web caching (network) to data access and rendering performance in the client (end-user). By distinguishing popular data management systems by data model, consistency guarantees, and other dimensions of interest, this book provides an abstract framework for reasoning about the overall design space and the individual positions claimed by each of the systems therein. Building on this classification, this book further presents an application-driven decision guidance tool that breaks the process of choosing a set of viable system candidates for a given application scenario down into a straightforward decision tree.




Stabilization, Safety, and Security of Distributed Systems


Book Description

This book constitutes the refereed proceedings of the 19th International Symposium on Stabilization, Safety, and Security of Distributed Systems, SSS 2017, held in Boston, MA, USA, in November 2017. The 29 revised full papers presented together with 8 revised short papers were carefully reviewed and selected from 68 initial submissions. This year the Symposium was organized into three tracks reflecting major trends related to self-* systems: Stabilizing Systems: Theory and Practice: Distributed Computing and Communication Networks; and Computer Security and Information Privacy.




Cloud Service Benchmarking


Book Description

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.




Performance Characterization and Benchmarking


Book Description

This book constitutes the refereed post-proceedings of the 5th TPC Technology Conference, TPCTC 2013, held in Trento, Italy, in August 2013. It contains 7 selected peer-reviewed papers, a report from the TPC Public Relations Committee and one invited paper. The papers present novel ideas and methodologies in performance evaluation, measurement and characterization.




Advanced Methodologies and Technologies in Network Architecture, Mobile Computing, and Data Analytics


Book Description

From cloud computing to data analytics, society stores vast supplies of information through wireless networks and mobile computing. As organizations are becoming increasingly more wireless, ensuring the security and seamless function of electronic gadgets while creating a strong network is imperative. Advanced Methodologies and Technologies in Network Architecture, Mobile Computing, and Data Analytics highlights the challenges associated with creating a strong network architecture in a perpetually online society. Readers will learn various methods in building a seamless mobile computing option and the most effective means of analyzing big data. This book is an important resource for information technology professionals, software developers, data analysts, graduate-level students, researchers, computer engineers, and IT specialists seeking modern information on emerging methods in data mining, information technology, and wireless networks.




Performance Characterization and Benchmarking. Traditional to Big Data


Book Description

This book constitutes the refereed post-conference proceedings of the 6th TPC Technology Conference, TPCTC 2014, held in Hangzhou, China, in September 2014. It contains 12 selected peer-reviewed papers, a report from the TPC Public Relations Committee. 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). Over the last five years TPCTC has been held successfully in conjunction with VLDB.







Mastering Apache Hbase


Book Description

Unlock the Power of Scalable and Distributed Data Storage with "Mastering Apache HBase" In the rapidly evolving landscape of data management, the ability to efficiently handle massive amounts of data has become an indispensable skill. "Mastering Apache HBase" serves as your definitive guide to mastering one of the most powerful and flexible distributed NoSQL databases – Apache HBase. Whether you're a seasoned data professional or a newcomer to the world of big data, this book equips you with the knowledge and skills needed to harness the full potential of Apache HBase. About the Book: "Mastering Apache HBase" takes you on a comprehensive journey through the intricacies of this robust and versatile NoSQL database. From the fundamentals of installation and configuration to advanced topics such as performance tuning and integration with other Big Data tools, this book covers it all. Each chapter is meticulously crafted to provide a deep understanding of the concepts along with practical, real-world applications. Key Features: · Solid Foundation: Build a strong understanding by exploring the core concepts of Apache HBase, including its architecture, data model, and storage components. · Efficient Data Management: Learn how to create tables, insert and retrieve data, and implement effective data modeling strategies that maximize performance and flexibility. · Scalability and Distribution: Dive into the distributed nature of Apache HBase and discover techniques to scale your cluster horizontally, ensuring seamless growth as your data needs expand. · Advanced Techniques: Master advanced topics such as data versioning, coprocessors, security, and backup and recovery, enabling you to tackle complex scenarios with confidence. · Performance Optimization: Uncover strategies and best practices for optimizing the performance of your Apache HBase cluster, ensuring your applications run smoothly even at scale. · Integration with Ecosystem: Explore how Apache HBase seamlessly integrates with other Big Data tools like Apache Hadoop, Apache Spark, and Apache Hive, opening up possibilities for data analysis and processing. · Real-World Use Cases: Learn through practical examples and use cases from various industries, including social media, e-commerce, finance, and more, to understand how Apache HBase can solve real-world data challenges. · Expert Insights: Benefit from the experience of seasoned professionals who provide insights, tips, and recommendations garnered from their years of working with Apache HBase. Who This Book Is For: "Mastering Apache HBase" is designed for data engineers, database administrators, and anyone involved in managing and analyzing large volumes of data. Whether you're a developer looking to expand your skillset or an experienced professional aiming to deepen your understanding of distributed data storage, this book is your ultimate resource. © 2023 Cybellium Ltd. All rights reserved. www.cybellium.com




Advances in Knowledge Discovery and Management


Book Description

This book is a collection of representative and novel works in the field of data mining, knowledge discovery, clustering and classification. Discussing both theoretical and practical aspects of “Knowledge Discovery and Management” (KDM), it is intended for researchers interested in these fields, including PhD and MSc students, and researchers from public or private laboratories. The contributions included are extended and reworked versions of six of the best papers that were originally presented in French at the EGC’2016 conference held in Reims (France) in January 2016. This was the 16th edition of this successful conference, which takes place each year, and also featured workshops and other events with the aim of promoting exchanges between researchers and companies concerned with KDM and its applications in business, administration, industry and public organizations. For more details about the EGC society, please consult egc.asso.fr.