1,910 research outputs found

    Multiple streaming at the network edge

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    Streaming video over the Internet, including cellular networks, has now become commonplace. Network operators typically use multicasting or variations of multiple unicasting to deliver streams to the user terminal in a controlled fashion. An emerging alternative is P2P streaming, which is theoretically more scalable but suffers from other issues arising from the dynamic nature of the system. User’s terminals become streaming nodes but these are not constantly connected. Another issue is that they are based on logical overlays, which are not optimized for the physical underlay infrastructure. An important proposition is that of finding effective ways to increase the resilience of the overlay whilst at the same time not conflicting with the network. In this article we look at the combination of two techniques, multi-streaming (redundancy) and locality (network efficiency) in the context of both live and video-on-demand streaming. We introduce a new technique and assess it via a comparative, simulation-based study. We find that redundancy affects network utilization only marginally if traffic is kept at the edges via localization technique

    Dynamic 3D Network Data Visualization

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    Monitoring network traffic has always been an arduous and tedious task because of the complexity and sheer volume of network data that is being consistently generated. In addition, network growth and new technologies are rapidly increasing these levels of complexity and volume. An effective technique in understanding and managing a large dataset, such as network traffic, is data visualization. There are several tools that attempt to turn network traffic into visual stimuli. Many of these do so in 2D space and those that are 3D lack the ability to display network patterns effectively. Existing 3D network visualization tools lack user interaction, dynamic generation, and intuitiveness. This project proposes a user-friendly 3D network visualization application that creates both dynamic and interactive visuals. This application was built using the Bablyon.js graphics framework and uses anonymized data collected from a campus network

    Inferring undesirable behavior from P2P traffic analysis

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    While peer-to-peer (P2P) systems have emerged in popularity in recent years, their large-scale and complexity make them difficult to reason about. In this paper, we argue that systematic analysis of traffic characteristics of P2P systems can reveal a wealth of information about their behavior, and highlight potential undesirable activities that such systems may exhibit. As a first step to this end, we present an offline and semi-automated approach to detect undesirable behavior. Our analysis is applied on real traffic traces collected from a Point-of-Presence (PoP) of a national-wide ISP in which over 70% of the total traffic is due to eMule, a popular P2P file-sharing system. Flow-level measurements are aggregated into "samples" referring to the activity of each host during a time interval. We then employ a clustering technique to automatically and coarsely identify similar behavior across samples, and extensively use domain knowledge to interpret and analyze the resulting clusters. Our analysis shows several examples of undesirable behavior including evidence of DDoS attacks exploiting live P2P clients, significant amounts of unwanted traffic that may harm network performance, and instances where the performance of participating peers may be subverted due to maliciously deployed servers. Identification of such patterns can benefit network operators, P2P system developers, and actual end-user

    A Framework for Integrating Transportation Into Smart Cities

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    In recent years, economic, environmental, and political forces have quickly given rise to “Smart Cities” -- an array of strategies that can transform transportation in cities. Using a multi-method approach to research and develop a framework for smart cities, this study provides a framework that can be employed to: Understand what a smart city is and how to replicate smart city successes; The role of pilot projects, metrics, and evaluations to test, implement, and replicate strategies; and Understand the role of shared micromobility, big data, and other key issues impacting communities. This research provides recommendations for policy and professional practice as it relates to integrating transportation into smart cities
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