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This book presents several compact and fast methods for online traffic measurement of big network data. It describes challenges of online;
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management and cost saving Practical traffic and resilience measurement and QoS supervision Frameworks for performance analytics and network;
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This book was prepared as the Final Publication of COST Action IC0703 Data Traffic Monitoring and Analysis: theory, techniques, tools and;
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traffic data; 2) be able to make sense of network behavior for a spectrum of applications ranging from cybersecurity and network monitoring to;
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some practical issues of applying the models for urban traffic monitoring. This book presents three novel mobility data-driven urban;
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, security researcher Michael Collins shows you several techniques and tools for collecting and analyzing network traffic datasets. You'll understand;
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comprehensive understanding of network big data, efficient collection and management of network big data, distributed and scalable online analytics for;
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areas that can be improved using big data prediction: grid energy, road traffic networks and environmental health in smart cities. The big data;
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develops a financial evaluation methodology for big data opportunities based on key performance indicators for airline network planning departments.;
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measurements, wireless, management tools, audio and video traffic, peer-to-peer, traffic measurements, and measurements of anomalous and unwanted;
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-related data using methodologies such as the data fusion model, the big data mining approach, computer vision-enabled traffic sensing data;
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Networking for Big Data supplies an unprecedented look at cutting-edge research on the networking and communication aspects of Big Data;
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Networking for Big Data supplies an unprecedented look at cutting-edge research on the networking and communication aspects of Big Data;
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Fundamentals of Big Data Network Analysis for Research and Industry Hyunjoung Lee, Institute of Green Technology, Yonsei University;
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voicedata dynamic routing networks. These functions control a network's response to traffic demands and other stimuli, such as link failures or;
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scheduling and manipulation, input traffic and triggered actions, as well as some interesting use cases around big data, data center overlays, and;
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understanding and discuss the big data analytics applications for power systems diagnostics, operation and control. Recent developments in monitoring;
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defined networking (SDN) and network function virtualization (NFV) paradigms. For a network slice with a target traffic load, the E2E service;
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Computational Intelligence for Multimedia Big Data on the Cloud with Engineering Applications covers timely topics, including the neural;
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detection methods State-of-the-art approaches for mitigating DDos attacks using SDN Big data using Apache Hadoop for processing and analyzing;
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academic perspectives, the book targets the pain points in telecommunication networks and markets through big data. Designed for both;
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covers a wide range of topics, including advanced traffic data collection methods, big data analysis, mix-traffic characterization and modelling;
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analytics, traffic predictions, gender based classification on e-commerce data, recommender systems, Big Data regression with Apache Spark, visual;
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analytics, traffic predictions, gender based classification on e-commerce data, recommender systems, Big Data regression with Apache Spark, visual;
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of GPS-enabled vehicular data and social media data have rapidly contributed to better understanding and estimating the traffic network states;
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Data Network Design is a must have for anyone seriously involved in designing data networks. Together with the companion volume, Data;
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