Download or read book Traffic Measurement for Big Network Data written by Shigang Chen and published by Springer. This book was released on 2016-11-01 with total page 109 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Data Traffic Monitoring and Analysis written by Ernst Biersack and published by Springer. This book was released on 2013-03-02 with total page 370 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book was prepared as the Final Publication of COST Action IC0703 "Data Traffic Monitoring and Analysis: theory, techniques, tools and applications for the future networks". It contains 14 chapters which demonstrate the results, quality,and the impact of European research in the field of TMA in line with the scientific objective of the Action. The book is structured into three parts: network and topology measurement and modelling, traffic classification and anomaly detection, quality of experience.

Download or read book Traffic Measurement on the Internet written by Tao Li and published by Springer Science & Business Media. This book was released on 2012-08-30 with total page 87 pages. Available in PDF, EPUB and Kindle. Book excerpt: Traffic Measurement on the Internet presents several novel online measurement methods that are compact and fast. Traffic measurement provides critical real-world data for service providers and network administrations to perform capacity planning, accounting and billing, anomaly detection, and service provision. Statistical methods play important roles in many measurement functions including: system designing, model building, formula deriving, and error analyzing. One of the greatest challenges in designing an online measurement function is to minimize the per-packet processing time in order to keep up with the line speed of the modern routers. This book also introduces a challenging problem – the measurement of per-flow information in high-speed networks, as well as, the solution. The last chapter discusses origin-destination flow measurement.

Download or read book Proceedings of the 4th International Conference on Big Data Analytics for Cyber Physical System in Smart City Volume 1 written by Mohammed Atiquzzaman and published by Springer Nature. This book was released on 2023-07-04 with total page 823 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book gathers a selection of peer-reviewed papers presented at the 4th Big Data Analytics for Cyber-Physical System in Smart City (BDCPS 2022) conference, held in Bangkok, Thailand, on December 16–17. The contributions, prepared by an international team of scientists and engineers, cover the latest advances and challenges made in the field of big data analytics methods and approaches for the data-driven co-design of communication, computing, and control for smart cities. Given its scope, it offers a valuable resource for all researchers and professionals interested in big data, smart cities, and cyber-physical systems.

Download or read book Networking for Big Data written by Shui Yu and published by CRC Press. This book was released on 2015-07-28 with total page 416 pages. Available in PDF, EPUB and Kindle. Book excerpt: Networking for Big Data supplies an unprecedented look at cutting-edge research on the networking and communication aspects of Big Data. Starting with a comprehensive introduction to Big Data and its networking issues, it offers deep technical coverage of both theory and applications.The book is divided into four sections: introduction to Big Data,

Download or read book ECCWS 2018 17th European Conference on Cyber Warfare and Security V2 written by Audun Jøsang and published by Academic Conferences and publishing limited. This book was released on 2018-06-21 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Big Data Analytics in Cybersecurity written by Onur Savas and published by CRC Press. This book was released on 2017-09-18 with total page 336 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Big Data Applications in the Telecommunications Industry written by Ouyang, Ye and published by IGI Global. This book was released on 2016-12-28 with total page 231 pages. Available in PDF, EPUB and Kindle. Book excerpt: The growing presence of smart phones and smart devices has caused significant changes to wireless networks. With the ubiquity of these technologies, there is now increasingly more available data for mobile operators to utilize. Big Data Applications in the Telecommunications Industry is a comprehensive reference source for the latest scholarly material on the use of data analytics to study wireless networks and examines how these techniques can increase reliability and profitability, as well as network performance and connectivity. Featuring extensive coverage on relevant topics, such as accessibility, traffic data, and customer satisfaction, this publication is ideally designed for engineers, students, professionals, academics, and researchers seeking innovative perspectives on data science and wireless network communications.

Download or read book Analysis of Travel Patterns from Cellular Network Data written by Nils Breyer and published by Linköping University Electronic Press. This book was released on 2019-05-29 with total page 32 pages. Available in PDF, EPUB and Kindle. Book excerpt: Traffic planners are facing a big challenge with an increasing demand for mobility and a need to drastically reduce the environmental impacts of the transportation system at the same time. The transportation system therefore needs to become more efficient, which requires a good understanding about the actual travel patterns. Data from travel surveys and traffic counts is expensive to collect and gives only limited insights on travel patterns. Cellular network data collected in the mobile operators infrastructure is a promising data source which can provide new ways of obtaining information relevant for traffic analysis. It can provide large-scale observations of travel patterns independent of the travel mode used and can be updated easier than other data sources. In order to use cellular network data for traffic analysis it needs to be filtered and processed in a way that preserves privacy of individuals and takes the low resolution of the data in space and time into account. The research of finding appropriate algorithms is ongoing and while substantial progress has been achieved, there is a still a large potential for better algorithms and ways to evaluate them. The aim of this thesis is to analyse the potential and limitations of using cellular network data for traffic analysis. In the three papers included in the thesis, contributions are made to the trip extraction, travel demand and route inference steps part of a data-driven traffic analysis processing chain. To analyse the performance of the proposed algorithms, a number of datasets from different cellular network operators are used. The results obtained using different algorithms are compared to each other as well as to other available data sources. A main finding presented in this thesis is that large-scale cellular network data can be used in particular to infer travel demand. In a study of data for the municipality of Norrköping, the results from cellular network data resemble the travel demand model currently used by the municipality, while adding more details such as time profiles which are currently not available to traffic planners. However, it is found that all later traffic analysis results from cellular network data can differ to a large extend based on the choice of algorithm used for the first steps of data filtering and trip extraction. Particular difficulties occur with the detection of short trips (less than 2km) with a possible under-representation of these trips affecting the subsequent traffic analysis.

Download or read book Machine Learning for Cyber Security written by Yuan Xu and published by Springer Nature. This book was released on 2023-01-12 with total page 707 pages. Available in PDF, EPUB and Kindle. Book excerpt: The three-volume proceedings set LNCS 13655,13656 and 13657 constitutes the refereedproceedings of the 4th International Conference on Machine Learning for Cyber Security, ML4CS 2022, which taking place during December 2–4, 2022, held in Guangzhou, China. The 100 full papers and 46 short papers were included in these proceedings were carefully reviewed and selected from 367 submissions.

Download or read book Driving Scientific and Engineering Discoveries Through the Convergence of HPC Big Data and AI written by Jeffrey Nichols and published by Springer Nature. This book was released on 2020-12-22 with total page 555 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the revised selected papers of the 17th Smoky Mountains Computational Sciences and Engineering Conference, SMC 2020, held in Oak Ridge, TN, USA*, in August 2020. The 36 full papers and 1 short paper presented were carefully reviewed and selected from a total of 94 submissions. The papers are organized in topical sections of computational applications: converged HPC and artificial intelligence; system software: data infrastructure and life cycle; experimental/observational applications: use cases that drive requirements for AI and HPC convergence; deploying computation: on the road to a converged ecosystem; scientific data challenges. *The conference was held virtually due to the COVID-19 pandemic.

Download or read book Database Systems for Advanced Applications written by Christian S. Jensen and published by Springer Nature. This book was released on 2021-04-06 with total page 683 pages. Available in PDF, EPUB and Kindle. Book excerpt: The three-volume set LNCS 12681-12683 constitutes the proceedings of the 26th International Conference on Database Systems for Advanced Applications, DASFAA 2021, held in Taipei, Taiwan, in April 2021. The total of 156 papers presented in this three-volume set was carefully reviewed and selected from 490 submissions. The topic areas for the selected papers include information retrieval, search and recommendation techniques; RDF, knowledge graphs, semantic web, and knowledge management; and spatial, temporal, sequence, and streaming data management, while the dominant keywords are network, recommendation, graph, learning, and model. These topic areas and keywords shed the light on the direction where the research in DASFAA is moving towards. Due to the Corona pandemic this event was held virtually.

Download or read book Seeing Cities Through Big Data written by Piyushimita (Vonu) Thakuriah and published by Springer. This book was released on 2016-10-07 with total page 554 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book introduces the latest thinking on the use of Big Data in the context of urban systems, including research and insights on human behavior, urban dynamics, resource use, sustainability and spatial disparities, where it promises improved planning, management and governance in the urban sectors (e.g., transportation, energy, smart cities, crime, housing, urban and regional economies, public health, public engagement, urban governance and political systems), as well as Big Data’s utility in decision-making, and development of indicators to monitor economic and social activity, and for urban sustainability, transparency, livability, social inclusion, place-making, accessibility and resilience.

Download or read book Towards Ideal Network Traffic Measurement written by Qi Zhao and published by . This book was released on 2007 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: With the emergence of computer networks as one of the primary platforms of communication, and with their adoption for an increasingly broad range of applications, there is a growing need for high-quality network traffic measurements to better understand, characterize and engineer the network behaviors. Due to the inherent lack of fine-grained measurement capabilities in the original design of the Internet, it does not have enough data or information to compute or even approximate.

Download or read book Intelligent Vehicular Networks and Communications written by Anand Paul and published by Elsevier. This book was released on 2016-09-02 with total page 244 pages. Available in PDF, EPUB and Kindle. Book excerpt: Intelligent Vehicular Network and Communications: Fundamentals, Architectures and Solutions begins with discussions on how the transportation system has transformed into today's Intelligent Transportation System (ITS). It explores the design goals, challenges, and frameworks for modeling an ITS network, discussing vehicular network model technologies, mobility management architectures, and routing mechanisms and protocols. It looks at the Internet of Vehicles, the vehicular cloud, and vehicular network security and privacy issues. The book investigates cooperative vehicular systems, a promising solution for addressing current and future traffic safety needs, also exploring cooperative cognitive intelligence, with special attention to spectral efficiency, spectral scarcity, and high mobility. In addition, users will find a thorough examination of experimental work in such areas as Controller Area Network protocol and working function of On Board Unit, as well as working principles of roadside unit and other infrastructural nodes. Finally, the book examines big data in vehicular networks, exploring various business models, application scenarios, and real-time analytics, concluding with a look at autonomous vehicles. - Proposes cooperative, cognitive, intelligent vehicular networks - Examines how intelligent transportation systems make more efficient transportation in urban environments - Outlines next generation vehicular networks technology

Download or read book Traffic Monitoring and Analysis written by Moritz Steiner and published by Springer. This book was released on 2015-04-16 with total page 249 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 7th International Workshop on Traffic Monitoring and Analysis, TMA 2015, held in Barcelona, Spain, in April 2015. The 16 full papers presented in this volume were carefully reviewed and selected from 54 submissions. The contributions are organized in topical sections on measurement tools and methods; mobile and wireless; Web; security; and new protocols.

Download or read book Scalable and Flexible Network wide Traffic Measurement written by Guanyao Huang and published by . This book was released on 2012 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: This thesis addresses the challenges and problems in network-wide traffic measurement. Network-wide traffic measurement faces two main challenges: how to improve local measurement accuracy under limited resources, and how to coordinate distributed monitors for global monitoring purposes. We first consider global iceberg detection as a measurement case study. We propose to combine uniform sampling and distributed sketches to detect and estimate both local elephants and global icebergs. Our observations and results provide a strong motivation for developing a scalable and flexible network-wide measurement framework that can best utilize the distributed monitors in the networks. To address these challenges, we propose, model, and analyze measurement-aware routing schemes which combines traffic measurement and routing. In the first part of dissertation we address the problem of global iceberg detection in distributed streams. While previous work has concentrated on measuring icebergs in the non-distributed streaming case or in the non-streaming distributed case, we present a general framework that allows for distributed processing across multiple streams of data. We compare several of the state-of-the-art streaming algorithms for estimating local elephants in the individual streams. However, since an iceberg may be hidden by being distributed across many different streams, we add a sampling component to handle such cases. We provide a novel taxonomy of current sketches and perform a thorough analysis of the strengths and weaknesses of each scheme under various QoS metrics, using both real and synthetic Internet trace data. We also discuss the implications for the future sketch design. In the second part of dissertation we propose MeasuRouting, a framework which combines routing and measurement. Previous research in network-wide traffic measurement focused on deriving a placement of monitors in order to maximize the monitoring utility under a fixed traffic routing. However, both traffic characteristics and measurement objectives can dynamically change over time, rendering a previously optimal placement strategy suboptimal. In contrary, MeasuRouting strategically routes traffic flows for better measurement. The main challenge for MeasuRouting is to work within the constraints of existing intra-domain traffic engineering operations. To solve it, MeasuRouting differentially routes components of an aggregate flow while ensuring that the aggregate routing is compliant to original traffic engineering objectives. We present the theoretical framework for MeasuRouting, and showcase the utility enhancement for both synthetic and practical monitoring applications. The third part of dissertation presents MMPR (Measurement-aware Monitor Placement and Routing) framework that jointly optimizes monitor placement and MeasuRouting strategy. Neither MeasuRouting nor monitor placement problem alone suffices in real measurement scenarios, since not only the number of deployed monitors is limited, but also the traffic characteristics and measurement objectives are constantly changing. The main challenge of MMPR is to decouple the relevant decision variables and adhere to the traffic engineering constraints. We formulate it as an MILP (Mixed Integer Linear Programming) problem and propose several heuristic algorithms to approximate the optimal solution and reduce the computation complexity. Through experiments using real traces and topologies, we show that our heuristic solutions can achieve measurement gains that are quite close to the optimal solutions, while significantly reducing the computation times. Lastly, we discuss how MeasuRouting can be implemented on OpenFlow testbed and address practical deployment issues. Implementing DMR (Dynamic Measurement-aware Routing) in practice is riddled with three major challenges: 1) How to dynamically assess the importance of traffic flows? 2) How to aggregate flows (and hence take a common action for them) in order to conserve routing table entries? and 3) How to achieve traffic routing/rerouting in a manner that is least disruptive to normal network performance while maximizing the measurement utility? We take a closer look at these challenges and discuss how they manifest for different types of networks. Through an OpenFlow prototype, we show how DMR can be applied in enterprise networks. Using global iceberg detection & capture as a driving application, we demonstrate how our solutions successfully route suspected iceberg flows to a DPI box for further processing, while preserving a balanced load distribution in the overall network. The contribution of this thesis to network traffic measurement are two folds. First, we study one specific application, global iceberg detection in distributed streams, to illustrate real-world problems which request "network-wide" traffic measurement. The proposed combination of local sketch and uniform sampling can better capture global iceberg. Secondly, we extensively study MeasuRouting, a framework that utilizes "routing" for better traffic measurement. The framework, along with its extension MMPR and implementation DMR, opens another direction for network-wide traffic measurement.