192 research outputs found

    The QUIC Fix for Optimal Video Streaming

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    Within a few years of its introduction, QUIC has gained traction: a significant chunk of traffic is now delivered over QUIC. The networking community is actively engaged in debating the fairness, performance, and applicability of QUIC for various use cases, but these debates are centered around a narrow, common theme: how does the new reliable transport built on top of UDP fare in different scenarios? Support for unreliable delivery in QUIC remains largely unexplored. The option for delivering content unreliably, as in a best-effort model, deserves the QUIC designers' and community's attention. We propose extending QUIC to support unreliable streams and present a simple approach for implementation. We discuss a simple use case of video streaming---an application that dominates the overall Internet traffic---that can leverage the unreliable streams and potentially bring immense benefits to network operators and content providers. To this end, we present a prototype implementation that, by using both the reliable and unreliable streams in QUIC, outperforms both TCP and QUIC in our evaluations.Comment: Published to ACM CoNEXT Workshop on the Evolution, Performance, and Interoperability of QUIC (EPIQ

    The growing complexity of content delivery networks: Challenges and implications for the Internet ecosystem

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    Since the commercialization of the Internet, content and related applications, including video streaming, news, advertisements, and social interaction have moved online. It is broadly recognized that the rise of all of these different types of content (static and dynamic, and increasingly multimedia) has been one of the main forces behind the phenomenal growth of the Internet, and its emergence as essential infrastructure for how individuals across the globe gain access to the content sources they want. To accelerate the delivery of diverse content in the Internet and to provide commercial-grade performance for video delivery and the Web, Content Delivery Networks (CDNs) were introduced. This paper describes the current CDN ecosystem and the forces that have driven its evolution. We outline the different CDN architectures and consider their relative strengths and weaknesses. Our analysis highlights the role of location, the growing complexity of the CDN ecosystem, and their relationship to and implications for interconnection markets.EC/H2020/679158/EU/Resolving the Tussle in the Internet: Mapping, Architecture, and Policy Making/ResolutioNe

    MBA: A market-based approach to data allocation and migration for cloud database

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    With the coming shift to cloud computing, cloud database is emerging to provide database service over the Internet. In the cloud-based environment, data are distributed at internet scale and the system needs to handle a huge number of user queries simultaneously without delay. How data are distributed among the servers has a crucial impact on the query load distribution and the system response time. In this paper, we propose a market-based control method, called MBA, to achieve query load balance via reasonable data distribution. In MBA, database nodes are treated as traders in a market, and certain market rules are used to intelligently decide data allocation and migration. We built a prototype system and conducted extensive experiments. Experimental results show that the MBA method signicantly improves system performance in terms of average query response time and fairness

    Cloud-based Content Distribution on a Budget

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    To leverage the elastic nature of cloud computing, a solution provider must be able to accurately gauge demand for its offering. For applications that involve swarm-to-cloud interactions, gauging such demand is not straightforward. In this paper, we propose a general framework, analyze a mathematical model, and present a prototype implementation of a canonical swarm-to-cloud application, namely peer-assisted content delivery. Our system – called Cyclops – dynamically adjusts the off-cloud bandwidth consumed by content servers (which represents the bulk of the provider's cost) to feed a set of swarming clients, based on a feedback signal that gauges the real-time health of the swarm. Our extensive evaluation of Cyclops in a variety of settings – including controlled PlanetLab and live Internet experiments involving thousands of users – show significant reduction in content distribution costs (by as much as two orders of magnitude) when compared to non-feedback-based swarming solutions, with minor impact on content delivery times

    The Internet Ecosystem: The Potential for Discrimination

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    Symposium: Rough Consensus and Running Code: Integrating Engineering Principles into Internet Policy Debates, held at the University of Pennsylvania\u27s Center for Technology Innovation and Competition on May 6-7, 2010. This Article explores how the emerging Internet architecture of cloud computing, content distribution networks, private peering and data-center services can simultaneously foster a perception of unfair network access while at the same time enabling significant competition for services, content, and innovation. A key enabler of these changes is the emergence of technologies that lower the barrier for entry in developing and deploying new services. Another is the design of successful Internet applications, which already accommodate the variation in service afforded by the current Internet. Regulators should be aware of the potential for anti-competitive practices in this broader Internet Ecosystem, but should carefully consider the effects of regulation on that ecosystem

    The Economics of Net Neutrality: Implications of Priority Pricing in Access Networks

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    This work systematically analyzes Net Neutrality from an economic point of view. To this end a framework is developed which helps to structure the Net Neutrality debate. Furthermore, the introduction of prioritization is studied by analyzing potential effects of Quality of Service (QoS) on Content and Service Providers (CSPs) and Internet Users (IUs)
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