P2p Techniques For Decentralized Applications
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Author | : Esther Pacitti |
Publisher | : Springer Nature |
Total Pages | : 90 |
Release | : 2022-06-01 |
Genre | : Computers |
ISBN | : 3031018885 |
As an alternative to traditional client-server systems, Peer-to-Peer (P2P) systems provide major advantages in terms of scalability, autonomy and dynamic behavior of peers, and decentralization of control. Thus, they are well suited for large-scale data sharing in distributed environments. Most of the existing P2P approaches for data sharing rely on either structured networks (e.g., DHTs) for efficient indexing, or unstructured networks for ease of deployment, or some combination. However, these approaches have some limitations, such as lack of freedom for data placement in DHTs, and high latency and high network traffic in unstructured networks. To address these limitations, gossip protocols which are easy to deploy and scale well, can be exploited. In this book, we will give an overview of these different P2P techniques and architectures, discuss their trade-offs, and illustrate their use for decentralizing several large-scale data sharing applications. Table of Contents: P2P Overlays, Query Routing, and Gossiping / Content Distribution in P2P Systems / Recommendation Systems / Top-k Query Processing in P2P Systems
Author | : Esther Pacitti |
Publisher | : Morgan & Claypool Publishers |
Total Pages | : 106 |
Release | : 2012-04-15 |
Genre | : Technology & Engineering |
ISBN | : 1608458237 |
As an alternative to traditional client-server systems, Peer-to-Peer (P2P) systems provide major advantages in terms of scalability, autonomy and dynamic behavior of peers, and decentralization of control. Thus, they are well suited for large-scale data sharing in distributed environments. Most of the existing P2P approaches for data sharing rely on either structured networks (e.g., DHTs) for efficient indexing, or unstructured networks for ease of deployment, or some combination. However, these approaches have some limitations, such as lack of freedom for data placement in DHTs, and high latency and high network traffic in unstructured networks. To address these limitations, gossip protocols which are easy to deploy and scale well, can be exploited. In this book, we will give an overview of these different P2P techniques and architectures, discuss their trade-offs, and illustrate their use for decentralizing several large-scale data sharing applications. Table of Contents: P2P Overlays, Query Routing, and Gossiping / Content Distribution in P2P Systems / Recommendation Systems / Top-k Query Processing in P2P Systems
Author | : Quang Hieu Vu |
Publisher | : Springer Science & Business Media |
Total Pages | : 330 |
Release | : 2009-10-20 |
Genre | : Computers |
ISBN | : 3642035140 |
Peer-to-peer (P2P) technology, or peer computing, is a paradigm that is viewed as a potential technology for redesigning distributed architectures and, consequently, distributed processing. Yet the scale and dynamism that characterize P2P systems demand that we reexamine traditional distributed technologies. A paradigm shift that includes self-reorganization, adaptation and resilience is called for. On the other hand, the increased computational power of such networks opens up completely new applications, such as in digital content sharing, scientific computation, gaming, or collaborative work environments. In this book, Vu, Lupu and Ooi present the technical challenges offered by P2P systems, and the means that have been proposed to address them. They provide a thorough and comprehensive review of recent advances on routing and discovery methods; load balancing and replication techniques; security, accountability and anonymity, as well as trust and reputation schemes; programming models and P2P systems and projects. Besides surveying existing methods and systems, they also compare and evaluate some of the more promising schemes. The need for such a book is evident. It provides a single source for practitioners, researchers and students on the state of the art. For practitioners, this book explains best practice, guiding selection of appropriate techniques for each application. For researchers, this book provides a foundation for the development of new and more effective methods. For students, it is an overview of the wide range of advanced techniques for realizing effective P2P systems, and it can easily be used as a text for an advanced course on Peer-to-Peer Computing and Technologies, or as a companion text for courses on various subjects, such as distributed systems, and grid and cluster computing.
Author | : Jens Teubner |
Publisher | : Springer Nature |
Total Pages | : 104 |
Release | : 2022-05-31 |
Genre | : Computers |
ISBN | : 3031018494 |
Roughly a decade ago, power consumption and heat dissipation concerns forced the semiconductor industry to radically change its course, shifting from sequential to parallel computing. Unfortunately, improving performance of applications has now become much more difficult than in the good old days of frequency scaling. This is also affecting databases and data processing applications in general, and has led to the popularity of so-called data appliances—specialized data processing engines, where software and hardware are sold together in a closed box. Field-programmable gate arrays (FPGAs) increasingly play an important role in such systems. FPGAs are attractive because the performance gains of specialized hardware can be significant, while power consumption is much less than that of commodity processors. On the other hand, FPGAs are way more flexible than hard-wired circuits (ASICs) and can be integrated into complex systems in many different ways, e.g., directly in the network for a high-frequency trading application. This book gives an introduction to FPGA technology targeted at a database audience. In the first few chapters, we explain in detail the inner workings of FPGAs. Then we discuss techniques and design patterns that help mapping algorithms to FPGA hardware so that the inherent parallelism of these devices can be leveraged in an optimal way. Finally, the book will illustrate a number of concrete examples that exploit different advantages of FPGAs for data processing. Table of Contents: Preface / Introduction / A Primer in Hardware Design / FPGAs / FPGA Programming Models / Data Stream Processing / Accelerated DB Operators / Secure Data Processing / Conclusions / Bibliography / Authors' Biographies / Index
Author | : Mohammad Sadoghi |
Publisher | : Springer Nature |
Total Pages | : 122 |
Release | : 2022-05-31 |
Genre | : Computers |
ISBN | : 3031018702 |
The last decade has brought groundbreaking developments in transaction processing. This resurgence of an otherwise mature research area has spurred from the diminishing cost per GB of DRAM that allows many transaction processing workloads to be entirely memory-resident. This shift demanded a pause to fundamentally rethink the architecture of database systems. The data storage lexicon has now expanded beyond spinning disks and RAID levels to include the cache hierarchy, memory consistency models, cache coherence and write invalidation costs, NUMA regions, and coherence domains. New memory technologies promise fast non-volatile storage and expose unchartered trade-offs for transactional durability, such as exploiting byte-addressable hot and cold storage through persistent programming that promotes simpler recovery protocols. In the meantime, the plateauing single-threaded processor performance has brought massive concurrency within a single node, first in the form of multi-core, and now with many-core and heterogeneous processors. The exciting possibility to reshape the storage, transaction, logging, and recovery layers of next-generation systems on emerging hardware have prompted the database research community to vigorously debate the trade-offs between specialized kernels that narrowly focus on transaction processing performance vs. designs that permit transactionally consistent data accesses from decision support and analytical workloads. In this book, we aim to classify and distill the new body of work on transaction processing that has surfaced in the last decade to navigate researchers and practitioners through this intricate research subject.
Author | : Amit Sheth |
Publisher | : Springer Nature |
Total Pages | : 159 |
Release | : 2022-05-31 |
Genre | : Computers |
ISBN | : 303101894X |
After the traditional document-centric Web 1.0 and user-generated content focused Web 2.0, Web 3.0 has become a repository of an ever growing variety of Web resources that include data and services associated with enterprises, social networks, sensors, cloud, as well as mobile and other devices that constitute the Internet of Things. These pose unprecedented challenges in terms of heterogeneity (variety), scale (volume), and continuous changes (velocity), as well as present corresponding opportunities if they can be exploited. Just as semantics has played a critical role in dealing with data heterogeneity in the past to provide interoperability and integration, it is playing an even more critical role in dealing with the challenges and helping users and applications exploit all forms of Web 3.0 data. This book presents a unified approach to harness and exploit all forms of contemporary Web resources using the core principles of ability to associate meaning with data through conceptual or domain models and semantic descriptions including annotations, and through advanced semantic techniques for search, integration, and analysis. It discusses the use of Semantic Web standards and techniques when appropriate, but also advocates the use of lighter weight, easier to use, and more scalable options when they are more suitable. The authors' extensive experience spanning research and prototypes to development of operational applications and commercial technologies and products guide the treatment of the material. Table of Contents: Role of Semantics and Metadata / Types and Models of Semantics / Annotation -- Adding Semantics to Data / Semantics for Enterprise Data / Semantics for Services / Semantics for Sensor Data / Semantics for Social Data / Semantics for Cloud Computing / Semantics for Advanced Applications
Author | : Foto Afrati |
Publisher | : Springer Nature |
Total Pages | : 229 |
Release | : 2022-11-10 |
Genre | : Computers |
ISBN | : 3031018591 |
The topic of using views to answer queries has been popular for a few decades now, as it cuts across domains such as query optimization, information integration, data warehousing, website design, and, recently, database-as-a-service and data placement in cloud systems. This book assembles foundational work on answering queries using views in a self-contained manner, with an effort to choose material that constitutes the backbone of the research. It presents efficient algorithms and covers the following problems: query containment; rewriting queries using views in various logical languages; equivalent rewritings and maximally contained rewritings; and computing certain answers in the data-integration and data-exchange settings. Query languages that are considered are fragments of SQL, in particular, select-project-join queries, also called conjunctive queries (with or without arithmetic comparisons or negation), and aggregate SQL queries.
Author | : Venkatesh Ganti |
Publisher | : Springer Nature |
Total Pages | : 69 |
Release | : 2022-05-31 |
Genre | : Computers |
ISBN | : 3031018974 |
Data warehouses consolidate various activities of a business and often form the backbone for generating reports that support important business decisions. Errors in data tend to creep in for a variety of reasons. Some of these reasons include errors during input data collection and errors while merging data collected independently across different databases. These errors in data warehouses often result in erroneous upstream reports, and could impact business decisions negatively. Therefore, one of the critical challenges while maintaining large data warehouses is that of ensuring the quality of data in the data warehouse remains high. The process of maintaining high data quality is commonly referred to as data cleaning. In this book, we first discuss the goals of data cleaning. Often, the goals of data cleaning are not well defined and could mean different solutions in different scenarios. Toward clarifying these goals, we abstract out a common set of data cleaning tasks that often need to be addressed. This abstraction allows us to develop solutions for these common data cleaning tasks. We then discuss a few popular approaches for developing such solutions. In particular, we focus on an operator-centric approach for developing a data cleaning platform. The operator-centric approach involves the development of customizable operators that could be used as building blocks for developing common solutions. This is similar to the approach of relational algebra for query processing. The basic set of operators can be put together to build complex queries. Finally, we discuss the development of custom scripts which leverage the basic data cleaning operators along with relational operators to implement effective solutions for data cleaning tasks.
Author | : Xin Luna Dong |
Publisher | : Springer Nature |
Total Pages | : 178 |
Release | : 2022-05-31 |
Genre | : Computers |
ISBN | : 3031018532 |
The big data era is upon us: data are being generated, analyzed, and used at an unprecedented scale, and data-driven decision making is sweeping through all aspects of society. Since the value of data explodes when it can be linked and fused with other data, addressing the big data integration (BDI) challenge is critical to realizing the promise of big data. BDI differs from traditional data integration along the dimensions of volume, velocity, variety, and veracity. First, not only can data sources contain a huge volume of data, but also the number of data sources is now in the millions. Second, because of the rate at which newly collected data are made available, many of the data sources are very dynamic, and the number of data sources is also rapidly exploding. Third, data sources are extremely heterogeneous in their structure and content, exhibiting considerable variety even for substantially similar entities. Fourth, the data sources are of widely differing qualities, with significant differences in the coverage, accuracy and timeliness of data provided. This book explores the progress that has been made by the data integration community on the topics of schema alignment, record linkage and data fusion in addressing these novel challenges faced by big data integration. Each of these topics is covered in a systematic way: first starting with a quick tour of the topic in the context of traditional data integration, followed by a detailed, example-driven exposition of recent innovative techniques that have been proposed to address the BDI challenges of volume, velocity, variety, and veracity. Finally, it presents merging topics and opportunities that are specific to BDI, identifying promising directions for the data integration community.
Author | : Angela Bonifati |
Publisher | : Springer Nature |
Total Pages | : 166 |
Release | : 2022-06-01 |
Genre | : Computers |
ISBN | : 3031018648 |
Graph data modeling and querying arises in many practical application domains such as social and biological networks where the primary focus is on concepts and their relationships and the rich patterns in these complex webs of interconnectivity. In this book, we present a concise unified view on the basic challenges which arise over the complete life cycle of formulating and processing queries on graph databases. To that purpose, we present all major concepts relevant to this life cycle, formulated in terms of a common and unifying ground: the property graph data model—the pre-dominant data model adopted by modern graph database systems. We aim especially to give a coherent and in-depth perspective on current graph querying and an outlook for future developments. Our presentation is self-contained, covering the relevant topics from: graph data models, graph query languages and graph query specification, graph constraints, and graph query processing. We conclude by indicating major open research challenges towards the next generation of graph data management systems.