High-speed, in-band performance measurement instrumentation for next generation IP networks

Facilitating always-on instrumentation of Internet traffic for the purposes of performance measurement is crucial in order to enable accountability of resource usage and automated network control, management and optimisation. This has proven infeasible to date due to the lack of native measurement mechanisms that can form an integral part of the network‟s main forwarding operation. However, Internet Protocol version 6 (IPv6) specification enables the efficient encoding and processing of optional per-packet information as a native part of the network layer, and this constitutes a strong reason for IPv6 to be adopted as the ubiquitous next generation Internet transport. In this paper we present a very high-speed hardware implementation of in-line measurement, a truly native traffic instrumentation mechanism for the next generation Internet, which facilitates performance measurement of the actual data-carrying traffic at small timescales between two points in the network. This system is designed to operate as part of the routers' fast path and to incur an absolutely minimal impact on the network operation even while instrumenting traffic between the edges of very high capacity links. Our results show that the implementation can be easily accommodated by current FPGA technology, and real Internet traffic traces verify that the overhead incurred by instrumenting every packet over a 10 Gb/s operational backbone link carrying a typical workload is indeed negligible

An Internet Heartbeat

Obtaining sound inferences over remote networks via active or passive measurements is difficult. Active measurement campaigns face challenges of load, coverage, and visibility. Passive measurements require a privileged vantage point. Even networks under our own control too often remain poorly understood and hard to diagnose. As a step toward the democratization of Internet measurement, we consider the inferential power possible were the network to include a constant and predictable stream of dedicated lightweight measurement traffic. We posit an Internet "heartbeat," which nodes periodically send to random destinations, and show how aggregating heartbeats facilitates introspection into parts of the network that are today generally obtuse. We explore the design space of an Internet heartbeat, potential use cases, incentives, and paths to deployment

Characterization of P2P IPTV Traffic: Scaling Analysis

P2P IPTV applications arise on the Internet and will be massively used in the future. It is expected that P2P IPTV will contribute to increase the overall Internet traffic. In this context, it is important to measure the impact of P2P IPTV on the networks and to characterize this traffic. Dur- ing the 2006 FIFA World Cup, we performed an extensive measurement campaign. We measured network traffic generated by broadcasting soc- cer games by the most popular P2P IPTV applications, namely PPLive, PPStream, SOPCast and TVAnts. From the collected data, we charac- terized the P2P IPTV traffic structure at different time scales by using wavelet based transform method. To the best of our knowledge, this is the first work, which presents a complete multiscale analysis of the P2P IPTV traffic. Our results show that the scaling properties of the TCP traffic present periodic behavior whereas the UDP traffic is stationary and lead to long- range depedency characteristics. For all the applications, the download traffic has different characteristics than the upload traffic. The signaling traffic has a significant impact on the download traffic but it has negligible impact on the upload. Both sides of the traffic and its granularity has to be taken into account to design accurate P2P IPTV traffic models.Comment: 27p, submitted to a conferenc

A Survey on Internet Traffic Measurement and Analysis

As the number of Internet users increasing rapidly in this world, Internet traffic is also increased. In computer network traffic measurement is the process of measuring the amount and type of traffic on a particular network. Internet traffic measurement and analysis are mostly used to characterize and analysis of network usage and user behaviour, but faces the problem of scalability under the explosive growth of Internet traffic and high speed access. It is not easy to handle Tera and Pera-byte traffic data with single server. Scalable Internet traffic measurement and analysis is difficult because a large dataset requires matching commutating and storage resources. To analyse this traffic multiple tools are available. But they do not perform well when the traffic data size increase. As data grows it is necessary to increase the necessary infrastructure to process it. The distributed File System can be used for this purpose, but it has certain limitation such as scalability, availability and fault tolerant. Hadoop is popular parallel processing framework that is widely used for working with large datasets and it is an open source distributed computing platform having MapReduce for distributed processing and HDFS to store huge amount of data. In future work we will present a Hadoop-based traffic monitoring system that perform a multiple types of analysis on large amount of internet traffic in a scalable manner Keywords- Traffic monitoring, Hadoop, MapReduce, HDFS, NetFlow

Internet Traffic Measurement: Trends and Impact to Campus Network

Abstract— University of Lampung (Unila) is an Institution of Higher Education located in Bandar Lampung. Since 2016, Unila has deployed Internet Access Management (IAM) to guarantee the healthiness of the campus network, as well as to enhance the effectiveness of the bandwidth usage. This study focused on internet traffic measurement, conducted in Unila’s campus network during February 1 until February 29, 2016. Overall, this study shows user behavior on their application. The trend data of monthly most popular URL Categories accessed by users was; 1st Computers & Technology with 30032328 hits or 39.1%, the 2nd was Search Engines & Portals with 14214611 hits or 18.5%. There were around 30-40 % of internet traffic was use for Streaming Media activity, it proves that the existence of Streaming Media Activity in Campus Network which contribute to network congestion. During a month doing internet measurement, we identify the most active device/user that are the 1st was Aruba Wireless Controller with total traffic flow 40.45%, the 2nd was CCR-1 with 26.2%, the 3rd was CCR-2 with 16.9%, and the 4th was Digital Library Server with total flow was 0.6%. Monthly uplink traffic total flow was 5889.92 GB while downlink traffic total flow was 61041.35 GB. We made a recommendation to Unila management for implementing traffic provisioning especially on streaming media activity specific on access to Google Global Cache (GGC), to overcome network congestion during peak time period on working hours. Keywords—internet access management, internet traffic measurement; traffic tren

Where is My Next Hop ? The Case of Indian Ocean Islands

Internet has become a foundation of our modern society. However, all regions or countries do not have the same Internet access regarding quality especially in the Indian Ocean Area (IOA). To improve this quality it is important to have a deep knowledge of the Internet physical and logical topology and associated performance. However, these knowledges are not shared by Internet service providers. In this paper, we describe a large scale measurement study in which we deploy probes in different IOA countries, we generate network traces, develop a tool to extract useful information and analyze these information. We show that most of the IOA traffic exits through one point even if there exists multiple exit points