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Stream Data Processing: A Quality of Service Perspective

Author: Sharma Chakravarthy

Publisher: Springer

Published: 2009-05-08

Total Pages: 324

ISBN-13: 9780387710020

The systems used to process data streams and provide for the needs of stream-based applications are Data Stream Management Systems (DSMSs). This book presents a new paradigm to meet the needs of these applications, including a detailed discussion of the techniques proposed. Ii includes important aspects of a QoS-driven DSMS (Data Stream Management System) and introduces applications where a DSMS can be used and discusses needs beyond the stream processing model. It also discusses in detail the design and implementation of MavStream. This volume is primarily intended as a reference book for researchers and advanced-level students in computer science. It is also appropriate for practitioners in industry who are interested in developing applications.

Stream Data Processing

Author: H. D. Basler

Publisher:

Published: 1993

Total Pages: 0

ISBN-13: 9780387565422

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Traditional database management systems, widely used today, are not well-suited for a class of emerging applications. These applications, such as network management, sensor computing, and so on, need to continuously process large amounts of data coming in the form of a stream and in addition, meet stringent response time requirements. Support for handling QoS metrics, such as response time, memory usage, and throughput, is central to any system proposed for the above applications. Stream Data Processing: A Quality of Service Perspective (Modeling, Scheduling, Load Shedding, and Complex Event Processing), presents a new paradigm suitable for stream and complex event processing. This book covers a broad range of topics in stream data processing and includes detailed technical discussions of a number of proposed techniques from QoS perspective. This volume is intended as a text book for graduate courses and as a reference book for researchers, advanced-level students in computer sciences, and IT practitioners.

Stream Data Processing: A Quality of Service Perspective

Author: Sharma Chakravarthy

Publisher: Springer Science & Business Media

Published: 2009-04-09

Total Pages: 341

ISBN-13: 0387710035

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Data Stream Management

Author: Lukasz Golab

Publisher: Springer Nature

Published: 2022-06-01

Total Pages: 65

ISBN-13: 3031018370

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Many applications process high volumes of streaming data, among them Internet traffic analysis, financial tickers, and transaction log mining. In general, a data stream is an unbounded data set that is produced incrementally over time, rather than being available in full before its processing begins. In this lecture, we give an overview of recent research in stream processing, ranging from answering simple queries on high-speed streams to loading real-time data feeds into a streaming warehouse for off-line analysis. We will discuss two types of systems for end-to-end stream processing: Data Stream Management Systems (DSMSs) and Streaming Data Warehouses (SDWs). A traditional database management system typically processes a stream of ad-hoc queries over relatively static data. In contrast, a DSMS evaluates static (long-running) queries on streaming data, making a single pass over the data and using limited working memory. In the first part of this lecture, we will discuss research problems in DSMSs, such as continuous query languages, non-blocking query operators that continually react to new data, and continuous query optimization. The second part covers SDWs, which combine the real-time response of a DSMS by loading new data as soon as they arrive with a data warehouse's ability to manage Terabytes of historical data on secondary storage. Table of Contents: Introduction / Data Stream Management Systems / Streaming Data Warehouses / Conclusions

Database Systems for Advanced Applications

Author: Jeffrey Xu Yu

Publisher: Springer

Published: 2011-04-09

Total Pages: 604

ISBN-13: 3642201490

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This two volume set LNCS 6587 and LNCS 6588 constitutes the refereed proceedings of the 16th International Conference on Database Systems for Advanced Applications, DASFAA 2011, held in Saarbrücken, Germany, in April 2010. The 53 revised full papers and 12 revised short papers presented together with 2 invited keynote papers, 22 demonstration papers, 4 industrial papers, 8 demo papers, and the abstract of 1 panel discussion, were carefully reviewed and selected from a total of 225 submissions. The topics covered are social network, social network and privacy, data mining, probability and uncertainty, stream processing, graph, XML, XML and graph, similarity, searching and digital preservation, spatial queries, query processing, as well as indexing and high performance.

Spatio-Temporal Data Streams

Author: Zdravko Galić

Publisher: Springer

Published: 2016-08-26

Total Pages: 107

ISBN-13: 1493965751

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This SpringerBrief presents the fundamental concepts of a specialized class of data stream, spatio-temporal data streams, and demonstrates their distributed processing using Big Data frameworks and platforms. It explores a consistent framework which facilitates a thorough understanding of all different facets of the technology, from basic definitions to state-of-the-art techniques. Key topics include spatio-temporal continuous queries, distributed stream processing, SQL-like language embedding, and trajectory stream clustering. Over the course of the book, the reader will become familiar with spatio-temporal data streams management and data flow processing, which enables the analysis of huge volumes of location-aware continuous data streams. Applications range from mobile object tracking and real-time intelligent transportation systems to traffic monitoring and complex event processing. Spatio-Temporal Data Streams is a valuable resource for researchers studying spatio-temporal data streams and Big Data analytics, as well as data engineers and data scientists solving data management and analytics problems associated with this class of data.

Data and Applications Security and Privacy XXIX

Author: Pierangela Samarati

Publisher: Springer

Published: 2015-06-22

Total Pages: 365

ISBN-13: 3319208101

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This book constitutes the refereed proceedings of the 29th Annual IFIP WG 11.3 International Working Conference on Data and Applications Security and Privacy, DBSec 2015, held in Fairfax, VA, USA, in July 2015. The 18 revised full papers and 6 short papers presented were carefully reviewed and selected from 45 submissions. The papers are organized in the following topical sections: data anonymization and computation; access control and authorization; user privacy; authentication and information integration; privacy and trust; access control and usage policies; network and internet security; and information flow and inference.

Data and Applications Security and Privacy XXV

Author: Yingjiu Li

Publisher: Springer Science & Business Media

Published: 2011-06-30

Total Pages: 319

ISBN-13: 3642223478

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This book constitutes the refereed proceedings of the 25th IFIP WG 11.3 International Conference on Data and Applications Security and Privacy, DBSec 2011, held in Richmond, VA, USA, in July 2011. The 14 revised full papers and 9 short papers presented together with 3 invited lectures were carefully reviewed and selected from 37 submissions. The topics of these papers include access control, privacy-preserving data applications, data confidentiality and query verification, query and data privacy, authentication and secret sharing.

Multimedia Big Data Computing for IoT Applications

Author: Sudeep Tanwar

Publisher: Springer

Published: 2019-07-17

Total Pages: 477

ISBN-13: 9811387591

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This book considers all aspects of managing the complexity of Multimedia Big Data Computing (MMBD) for IoT applications and develops a comprehensive taxonomy. It also discusses a process model that addresses a number of research challenges associated with MMBD, such as scalability, accessibility, reliability, heterogeneity, and Quality of Service (QoS) requirements, presenting case studies to demonstrate its application. Further, the book examines the layered architecture of MMBD computing and compares the life cycle of both big data and MMBD. Written by leading experts, it also includes numerous solved examples, technical descriptions, scenarios, procedures, and algorithms.

Semantic Web

Author: Michael Workman

Publisher: Springer

Published: 2015-08-27

Total Pages: 229

ISBN-13: 3319166581

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This book examines recent developments in semantic systems that can respond to situations and environments and events. The contributors to this book cover how to design, implement and utilize disruptive technologies. The editor discusses the two fundamental sets of disruptive technologies: the development of semantic technologies including description logics, ontologies and agent frameworks; and the development of semantic information rendering and graphical forms of displays of high-density time-sensitive data to improve situational awareness. Beyond practical illustrations of emerging technologies, the editor proposes to utilize an incremental development method called knowledge scaffolding –a proven educational psychology technique for learning a subject matter thoroughly. The goal of this book is to help readers learn about managing information resources, from the ground up and reinforcing the learning as they read on.