Named Data Networking (NDN) is one of five projects funded by the U.S. National Science Foundation under its Future Internet Architecture Program. NDN has its roots in an earlier project, Content-Centric Networking (CCN), which Van Jacobson first publicly presented in 2006. The NDN project investigates Jacobson's proposed evolution from today's host-centric network architecture (IP) to a data-centric network architecture (NDN). This conceptually simple shift has far-reaching implications for how we design, develop, deploy, and use networks and applications. We describe the motivation and vision of this new architecture, and its basic components and operations. We also provide a snapshot of its current design, development status, and research challenges. More information about the project, including prototype implementations, publications, and annual reports, is available on named-data.net.
Since the emergence of peer-to-peer (P2P) networking in the late '90s, P2P applications have multiplied, evolved and established themselves as the leading 'growth app' of Internet traffic workload. In contrast to first-generation P2P networks which used well-defined port numbers, current P2P applications have the ability to disguise their existence through the use of arbitrary ports. As a result, reliable estimates of P2P traffic require examination of packet payload, a methodological landmine from legal, privacy, technical, logistic, and fiscal perspectives. Indeed, access to user payload is often rendered impossible by one of these factors, inhibiting trustworthy estimation of P2P traffic growth and dynamics. In this paper, we develop a systematic methodology to identify P2P flows at the transport layer, i.e., based on connection patterns of P2P networks, and without relying on packet payload. We believe our approach is the first method for characterizing P2P traffic using only knowledge of network dynamics rather than any user payload. To evaluate our methodology, we also develop a payload technique for P2P traffic identification, by reverse engineering and analyzing the nine most popular P2P protocols, and demonstrate its efficacy with the discovery of P2P protocols in our traces that were previously unknown to us. Finally, our results indicate that P2P traffic continues to grow unabatedly, contrary to reports in the popular media.
We introduce the area of remote physical device finger-
In a packet network, the terms bandwidth and throughput often characterize the amount of data that the network can transfer per unit of time. Bandwidth estimation is of interest to users wishing to optimize end-to-end transport performance, overlay network routing, and peer-to-peer file distribution. Techniques for accurate bandwidth estimation are also important for traffic engineering and capacity planning support. Existing bandwidth estimation tools measure one or more of three related metrics: capacity, available bandwidth, and bulk transfer capacity. Currently available bandwidth estimation tools employ a variety of strategies to measure these metrics. In this survey we review the recent bandwidth estimation literature focusing on underlying techniques and methodologies as well as open source bandwidth measurement tools.
Abstract-Recent reports in the popular media suggest a significant decrease in peer-to-peer (P2P) file-sharing traffic, attributed to the public's response to legal threats. Have we reached the end of the P2P revolution? In pursuit of legitimate data to verify this hypothesis, we embark on a more accurate measurement effort of P2P traffic at the link level. In contrast to previous efforts we introduce two novel elements in our methodology. First, we measure traffic of all known popular P2P protocols. Second, we go beyond the "known port" limitation by reverse engineering the protocols and identifying characteristic strings in the payload. We find that, if measured accurately, P2P traffic has never declined; indeed we have never seen the proportion of p2p traffic decrease over time (any change is an increase) in any of our data sources.
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