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Author: Shigang Chen
Publisher: Springer
ISBN: 3319473409
Category : Technology & Engineering
Languages : en
Pages : 109
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Book Description
This book presents several compact and fast methods for online traffic measurement of big network data. It describes challenges of online traffic measurement, discusses the state of the field, and provides an overview of the potential solutions to major problems. The authors introduce the problem of per-flow size measurement for big network data and present a fast and scalable counter architecture, called Counter Tree, which leverages a two-dimensional counter sharing scheme to achieve far better memory efficiency and significantly extend estimation range. Unlike traditional approaches to cardinality estimation problems that allocate a separated data structure (called estimator) for each flow, this book takes a different design path by viewing all the flows together as a whole: each flow is allocated with a virtual estimator, and these virtual estimators share a common memory space. A framework of virtual estimators is designed to apply the idea of sharing to an array of cardinality estimation solutions, achieving far better memory efficiency than the best existing work. To conclude, the authors discuss persistent spread estimation in high-speed networks. They offer a compact data structure called multi-virtual bitmap, which can estimate the cardinality of the intersection of an arbitrary number of sets. Using multi-virtual bitmaps, an implementation that can deliver high estimation accuracy under a very tight memory space is presented. The results of these experiments will surprise both professionals in the field and advanced-level students interested in the topic. By providing both an overview and the results of specific experiments, this book is useful for those new to online traffic measurement and experts on the topic.
Author: Shigang Chen
Publisher: Springer
ISBN: 3319473409
Category : Technology & Engineering
Languages : en
Pages : 109
Get Book Here
Book Description
This book presents several compact and fast methods for online traffic measurement of big network data. It describes challenges of online traffic measurement, discusses the state of the field, and provides an overview of the potential solutions to major problems. The authors introduce the problem of per-flow size measurement for big network data and present a fast and scalable counter architecture, called Counter Tree, which leverages a two-dimensional counter sharing scheme to achieve far better memory efficiency and significantly extend estimation range. Unlike traditional approaches to cardinality estimation problems that allocate a separated data structure (called estimator) for each flow, this book takes a different design path by viewing all the flows together as a whole: each flow is allocated with a virtual estimator, and these virtual estimators share a common memory space. A framework of virtual estimators is designed to apply the idea of sharing to an array of cardinality estimation solutions, achieving far better memory efficiency than the best existing work. To conclude, the authors discuss persistent spread estimation in high-speed networks. They offer a compact data structure called multi-virtual bitmap, which can estimate the cardinality of the intersection of an arbitrary number of sets. Using multi-virtual bitmaps, an implementation that can deliver high estimation accuracy under a very tight memory space is presented. The results of these experiments will surprise both professionals in the field and advanced-level students interested in the topic. By providing both an overview and the results of specific experiments, this book is useful for those new to online traffic measurement and experts on the topic.
Author: Wenjie Zhang
Publisher: Springer Nature
ISBN: 9819772419
Category :
Languages : en
Pages : 526
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Book Description
Author: National Research Council
Publisher: National Academies Press
ISBN: 0309168775
Category : Computers
Languages : en
Pages : 94
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Book Description
This report presents findings of a workshop featuring representatives of Internet Service Providers and others with access to data and insights about how the Internet performed on and immediately after the September 11 attacks. People who design and operate networks were asked to share data and their own preliminary analyses among participants in a closed workshop. They and networking researchers evaluated these inputs to synthesize lessons learned and derive suggestions for improvements in technology, procedures, and, as appropriate, policy.
Author: Onur Savas
Publisher: CRC Press
ISBN: 1498772161
Category : Business & Economics
Languages : en
Pages : 336
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Book Description
Big data is presenting challenges to cybersecurity. For an example, the Internet of Things (IoT) will reportedly soon generate a staggering 400 zettabytes (ZB) of data a year. Self-driving cars are predicted to churn out 4000 GB of data per hour of driving. Big data analytics, as an emerging analytical technology, offers the capability to collect, store, process, and visualize these vast amounts of data. Big Data Analytics in Cybersecurity examines security challenges surrounding big data and provides actionable insights that can be used to improve the current practices of network operators and administrators. Applying big data analytics in cybersecurity is critical. By exploiting data from the networks and computers, analysts can discover useful network information from data. Decision makers can make more informative decisions by using this analysis, including what actions need to be performed, and improvement recommendations to policies, guidelines, procedures, tools, and other aspects of the network processes. Bringing together experts from academia, government laboratories, and industry, the book provides insight to both new and more experienced security professionals, as well as data analytics professionals who have varying levels of cybersecurity expertise. It covers a wide range of topics in cybersecurity, which include: Network forensics Threat analysis Vulnerability assessment Visualization Cyber training. In addition, emerging security domains such as the IoT, cloud computing, fog computing, mobile computing, and cyber-social networks are examined. The book first focuses on how big data analytics can be used in different aspects of cybersecurity including network forensics, root-cause analysis, and security training. Next it discusses big data challenges and solutions in such emerging cybersecurity domains as fog computing, IoT, and mobile app security. The book concludes by presenting the tools and datasets for future cybersecurity research.
Author: My T. Thai
Publisher: CRC Press
ISBN: 1315396696
Category : Business & Economics
Languages : en
Pages : 253
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Book Description
This book presents recent developments on the theoretical, algorithmic, and application aspects of Big Data in Complex and Social Networks. The book consists of four parts, covering a wide range of topics. The first part of the book focuses on data storage and data processing. It explores how the efficient storage of data can fundamentally support intensive data access and queries, which enables sophisticated analysis. It also looks at how data processing and visualization help to communicate information clearly and efficiently. The second part of the book is devoted to the extraction of essential information and the prediction of web content. The book shows how Big Data analysis can be used to understand the interests, location, and search history of users and provide more accurate predictions of User Behavior. The latter two parts of the book cover the protection of privacy and security, and emergent applications of big data and social networks. It analyzes how to model rumor diffusion, identify misinformation from massive data, and design intervention strategies. Applications of big data and social networks in multilayer networks and multiparty systems are also covered in-depth.
Author: Gyamfi, Albert
Publisher: IGI Global
ISBN: 1522575200
Category : Computers
Languages : en
Pages : 336
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Book Description
Knowledge in its pure state is tacit in nature—difficult to formalize and communicate—but can be converted into codified form and shared through both social interactions and the use of IT-based applications and systems. Even though there seems to be considerable synergies between the resulting huge data and the convertible knowledge, there is still a debate on how the increasing amount of data captured by corporations could improve decision making and foster innovation through effective knowledge-sharing practices. Big Data and Knowledge Sharing in Virtual Organizations provides innovative insights into the influence of big data analytics and artificial intelligence and the tools, methods, and techniques for knowledge-sharing processes in virtual organizations. The content within this publication examines cloud computing, machine learning, and knowledge sharing. It is designed for government officials and organizations, policymakers, academicians, researchers, technology developers, and students.
Author: Mohammad Moshirpour
Publisher: Springer
ISBN: 3319602551
Category : Business & Economics
Languages : en
Pages : 168
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Book Description
This book addresses the impacts of various types of services such as infrastructure, platforms, software, and business processes that cloud computing and Big Data have introduced into business. Featuring chapters which discuss effective and efficient approaches in dealing with the inherent complexity and increasing demands in data science, a variety of application domains are covered. Various case studies by data management and analysis experts are presented in these chapters. Covered applications include banking, social networks, bioinformatics, healthcare, transportation and criminology. Highlighting the Importance of Big Data Management and Analysis for Various Applications will provide the reader with an understanding of how data management and analysis are adapted to these applications. This book will appeal to researchers and professionals in the field.
Author: A.Pasumpon Pandian
Publisher: Springer Nature
ISBN: 9811609659
Category : Technology & Engineering
Languages : en
Pages : 980
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Book Description
This book presents best selected research papers presented at the International Conference on Computer Networks, Big Data and IoT (ICCBI 2020), organized by Vaigai College Engineering, Madurai, Tamil Nadu, India, during 15–16 December 2020. The book covers original papers on computer networks, network protocols and wireless networks, data communication technologies and network security. The book is a valuable resource and reference for researchers, instructors, students, scientists, engineers, managers and industry practitioners in those important areas.
Author: Constantinos Dovrolis
Publisher: Springer
ISBN: 3540319662
Category : Computers
Languages : en
Pages : 385
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Book Description
Welcometothe6thInternationalWorkshoponPassiveandActiveMeasurement, held in Boston, Massuchusetts. PAM 2005 was organized by Boston University, with ?nancial support from Endace Measurement Systems and Intel. PAM continues to grow and mature as a venue for research in all aspects of Internet measurement. This trend is being driven by increasing interest and activity in the ?eld of Internet measurement. To accommodate the increasing interest in PAM, this year the workshop added a Steering Committee, whose members will rotate, to provide continuity and oversight of the PAM workshop series. PAMplaysaspecialroleinthemeasurementcommunity. Itemphasizespr- matic, relevant research in the area of network and Internet measurement. Its focus re?ects the increasing understanding that measurement is critical to e?- tive engineering of the Internet’s components. This is clearly a valuable role, as evidenced by the yearly increases in the number of submissions, interest in, and attendance at PAM. PAM received 84 submissions this year. Each paper was reviewed by three or four Program Committee (PC) members during the ?rst round. Papers that received con?icting scores were further reviewed by additional PC members or external reviewers (typically two). After all reviews were received, each paper with con?icting scores was discussed extensively by its reviewers, until a c- sensus was reached. The PC placed particular emphasis on selecting papers that were fresh and exciting research contributions. Also, strong preference was given to papers that included validation results based on real measurements.
Author: Jeffrey S. Beasley
Publisher: Pearson Education
ISBN: 0131363433
Category : Computers
Languages : en
Pages : 1029
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Book Description
Networking Second Edition Jeffrey S. Beasley This text provides a comprehensive look at computer networking from the point of view of the network administrator. It guides readers from an entry-level knowledge in computer networks to advanced concepts in Ethernet networks; router configuration; TCP/IP networks; local-, campus-, and wide-area network configuration; network security; optical networks; voice over IP; and industrial networks. Extensive examples on the Windows Server 2003/2008 configuration and system configuration for the Linux operating system are also included. A complete chapter is devoted to protecting and securing a network from potential network attacks. Topics include denial of service attacks, firewalls, intrusion detection, password cracking, packet sniffing, and analyzing unsecured data packets. Other key network security issues, such as configuring router access lists, configuring a virtual private network (VPN) connection, and securing wireless networks, are also covered. Router configuration is examined, ranging from an introduction to router configuration to configuring multiple routing protocols for intranet and Internet data traffic. Routing protocols key to basic network operations are examined, including static, RIP, IGRP, OSPF, EIGRP, and BGP. The discussions on routing protocols are accompanied with in-depth steps for configuring the router to run the protocol, verify operation, and troubleshoot the router. Key Pedagogical Features PROTOCOL ANALYZER SOFTWARE included with the text uses the Finisar Surveyor Demo. Examples of using the software to analyze data traffic are included throughout the text. CONFIGURING, ANALYZING, or TROUBLESHOOTING sections are included with each chapter to guide the reader through advanced techniques in networking. OBJECTIVES and INTRODUCTION at the beginning of each chapter clearly outline specific goals for the reader. EXTENSIVE PROBLEM SETS, SUMMARIES, and QUESTIONS AND PROBLEMS (including Critical Thinking questions) are found at the end of each chapter. KEY TERMS and their definitions are highlighted in the margins to foster inquisitiveness and ensure retention.
