Measurement Studies of End-to-End Congestion Control in the Internet

This page surveys measurement studies that shed light on the state of end-to-end congestion control in the Internet. It first motivates the topic, then moves on to the measurements themselves.

Future predictions

• Video Road Hogs Stir Fear of Internet Traffic Jam. Steve Lohr, New York Times, March 13, 2008.
  (An account might be needed to view this article...)
  "Projections that the increasing amount of data on the Internet will cause user demand to overwhelm the available capacity are disputed by many experts. At the current rate of growth, global Internet traffic cold guadruple by 2011."

• Study Warns of Internet Brownouts By 2010. Slashdot, November 19, 2007.
  "Our findings indicate that although core fiber and switching/routing resources will scale nicely to support virtually any conceivable user demand, Internet access infrastructure, specifically in North America, will likely cease to be adequate for supporting demand within the next three to five years."

TCP-friendly congestion control

• The Concerns about End-to-End Congestion Control page contains pointers to articles on the need for end-to-end congestion control, and a list of some potentially TCP-unfriendly protocols and applications.

• The TCP-Friendly Congestion Control page summarizes recent work on congestion control algorithms for non-TCP based applications, focusing on schemes that use the "TCP-friendly" equation.

• TBIT, the TCP Behavior Inference Tool, characterized the TCP implementations of (many) web servers in the Internet.

Internet traffic and weather

• IEPM, the Internet End-to-end Performance Monitoring Group, uses PingER to plot monthly stats of packet loss rates. SLAC's PingER data includes continent-to-continent and country-to-country loss rates between participating sites going back to April 2000, and a history of loss rates from SLAC since October 2000, showing the steady decrease in these packet loss rates over the last two years. Some traceroute results are also available from SLAC, NLANR, and IPPM.

• The Internet Traffic Report, charts global and regional packet-loss indexes. For February 2000, the Global Packet Loss statistic averaged 4% packet loss, and the North American Packet Loss statistic averaged 1% packet loss.
  For February 2001, the Global Packet Loss statistic averaged 2% packet loss, and the North American Packet Loss statistic averaged 2.3% packet loss (due to two routers with 100% packet loss rates).

• Internet quality of service assessment from Telcordia. They measure delays and bandwidth to the top 100 URLs, and to 100 random URLs.

• The Internet Weather Report has been discontinued, replaced by the Internet Average, which reports latency, packet loss, and reachability for the last day, week, or month. They also have yearly data from 1993 to the present. There is also a page of Event Advisories.

• The Internet Health Report reports on the latency (of establishing a TCP connection) between agents at eight major U.S. backbones, over the last hour or day.

• The distribution of packet drop rates from traces from the NIMI mesh in August, 2002, shows a median packet drop rate of 0.7%. Description of traces.

• CAIDA's Internet Measurement Infrastructure web page lists a number of Internet weather sites.

• Caida's Active Measurement Project includes realtime data reports showing, among other things, packet loss rates between pairs of nodes over the last 24 hours. The nodes are in the US, largely at NSF-supported High Performance Computing sites. The sparsity of color shows that most of the packet loss rates are less than 1%.

• Measurements of the distribution of round-trip times for an aggregate.

Bandwidth used by different traffic types

• CAIDA's Traffic Workload Overview plots statistics showing the relative bandwidth usage of TCP, UDP, ICMP, and other IP traffic at selected sites, for 1999. In addition, their Graphs of Ames Internet Exchange (AIX) traffic show the relative bandwidth usage of different traffic types from May 1999 to March 2000. In June 1999, measurements at backbone routers, edge routers, and major exchange points show 90-95% of the bytes belonging to TCP traffic.

• February 2001 measurements from a transatlantic link, showing that 95% of the bytes are from TCP. Follow-up mail gives more information.

• CAIDA's demonstration of the realtime monitoring of traffic flows by CoralReef shows traffic on the SDSC inbound link at CERFnet sorted by protocols, applications, flows, source and destination hosts, source and destination ASes, and source and destination countries.

• CAIDA's Mantra monitors the current state of multicast routing and of multicast routing protocols.

• Henning Schulzrinne's Long-Term Traffic Statistics page points to a range of traffic statistics, including statistics about the relative bandwidth of voice and data traffic, from 1998.

• Krishnamurthy et al's paper on On the Use and Performance of Content Distribution Networks reports an order of magnitude increase in the number of origin sites using CDNs (Content Distribution Networks) between 11/99 and 12/00.

• Gigandet et al's paper on The Inktomi Climate Lab models the network traffic load at proxy caches.

Multimedia traffic characterization

• The following paper presents a preliminary analysis of streaming media traffic originating from a popular Internet audio service:

  Art Mena and John Heidemann, An Empirical Study of Internet Audio Traffic, to appear in Proc. of IEEE Infocom 2000, March 2000.

• The following paper describes a tool for gathering traces of Internet multimedia traffic, and presents examples of the types of analysis the tool enables:

  Jacobus van der Merwe, Ramón Cáceres, Yang-hua Chu, and Cormac Sreenan, mmdump: A Tool for Monitoring Internet Multimedia Traffic, AT&T Labs-Research TR 00.2.1, February 2000.

Network Measurements at Specific Sites

• An OC-192 backbone link in 2006:
  W. John and S. Tafvelin, Analysis of Internet Backbone Traffic and Header Anomalies Observed, IMC 2007.
  This paper reports on packet size distribution, transport protocol breakdown (96-97\% TCP bytes), ECN use (not used), IP options (not used), TCP MSS and SACK options (widely used), and other properties of aggregate traffic.

• Sprint:
  • Packet Trace Analysis from Sprint ATL.
    Measurements include link utilization, number of active flows, traffic breakdown by protocol and by application, and packet size distribution, on traces from 2000 to 2005.

  • Chuck Fraleigh et al, Packet-Level Traffic Measurements from the Sprint IP Backbone, IEEE Network, November/December 2003, V.17 N.6.
    This paper includes measurements of traffic breakdown by application (e.g., web, peer-to-peer); packet size distribution; TCP round-trip times; and out-of-sequence packets. "We observe 1-6 percent of streaming traffic." In all cases, over 90 percent of the traffic is TCP.

  • S. Jaiswal et al, Measurement and Classification of Out-of-Sequence Packets in a Tier-1 IP Backbone, Infocom 2003, also IEEE/ACM Transactions on Networking 2007.
    "Our measurements show a relatively consistent rate of out-of-sequence packets of approximately 4%. We observe that a majority of out-of-sequence packets are retransmissions, with a smaller percentage resulting from in-network reordering." The traces are from 2002.

• SLAC: The daily and historical NETFLOW Status Report shows traffic breakdown by protocol, application, and SLAC program. 2005-2007.

• Internet2: Weekly Reports from Internet2 shows data about bulk TCP performance, protocol distribution, ECN-capable traffic, application types, and the like for traffic on Abilene. 2002-2007.

• R. Nelson, D. Lawson, and P. Lorier, Analysis of Long Duration Traces, CCR, January 2005. "Some typical analyses are presented, covering protocol mix, network trip times, and TCP flag analysis."

• The Tstat tool has been used to collect a range of TCP/IP statistics from traces on an access link in Italy, for 2000-2002. Statistics include IP protocol, TOS, and TTL fields, flow length in bytes or packets, port numbers, options, and advertised windows, MSS, flight size, out-of-sequence and duplicate burst sizes, and RTTs.

• 2007 Network Performance Statistics from the UW-Madison campus network. This includes traffic breakdowns by IP protocol, application, and access link bandwidth.

• Measurements from the University of Auckland for 2001 show information such as packet losses and throughput on the 4 Mbps access link to the 100 Mbps local network.

• Yubing Wang, Mark Claypool, et al, An Empirical Study of RealVideo Performance Across the Internet, IMW 2001.
  "Overall video performance is most influenced by the bandwidth of the end-user connection to the Internet, but high-bandwidth Internet connections are pushing the video performance bottleneck closer to the server."

• Dmitri Loguinov and H. Radha, Measurement Study of Low-bitrate Internet Video Streaming, ACM SIGCOMM Internet Measurement Workshop (IMW), November 2001.
  This paper studied packet-loss rates from a seven-month study of video traffic in the United States. Of the dial-up connections that were able to provide packet drop rates less than 15%, 75% experienced loss rates below 0.3%, and 91% experienced loss rates below 2%.

• Hao Jiang and C. Dovrolis's paper on Passive Estimation of TCP Round-Trip Times estimates the distribution of roundtrip-times, by connection and by byte, from several tcpdump traces.

• Mark Allman's A Web Server's View of the Transport Layer looks at path properties and TCP and HTTP protocol behavior from clients to a particular web server. The paper also reports on the range of round-trip times and of packet sizes.

• The MAWI Working Group Traffic Archive has trans-Pacific packet traces from 1999-2003, with each day's statistics giving the protocol breakdown and the ten biggest flows. Including outliers like June 18, 2000, when 57% of the packets were from DNS traffic.

• Michael S. Borella, Debbie Swider, Suleyman Uludag, Gregory B. Brewster, Internet Packet Loss: Measurement and Implications for End-to-End QoS, 1998.
  "We analyze a month of Internet packet loss statistics for speech transmission using three different sets of transmitter /receiver host pairs." The packet drop rates for the three paths, all in the U.S., ranged from 0.4% to 3.5%.

• Hari Balakrishnan, Venkata N. Padmanabhan, Srinivasan Seshan, Mark Stemm, Randy H. Katz, TCP Behavior of a Busy Internet Server: Analysis and Improvements, Infocom 1998.
  From 1996 traces from the web server for the Atlanta Olympic games, the total average packet drop rate was 0.5%.

• The Nature of the Beast: Recent Traffic Measurements from an Internet Backbone, from K Claffy, G. Miller, and K. Thompson, gives traffic measurements from the MCI backbone in 1998.

• Trends in Wide Area IP Traffic Patterns: A View from Ames Internet Exchange, by S. McCreary and KC Claffy, describes trends in measurements from May 1999 thru March 2000. The trends include decreases in RealAudio traffic, and increases in traffic from online games, Napster, and IPSec traffic.

Older Measurements

• Jean-Chrysostome Bolot, Characterizing End-to-End Packet Delay and Loss in the Internet, SIGCOMM, 1993.
  From small UDP probe packets sent at regular intervals on a path between France and the United States in 1992, the average packet loss rate ranged from 11% to 23%.

• Vern Paxson, Measurements and Analysis of End-to-End Internet Dynamics, 1997.
  Ack loss rates ranged from 1.3% (for traffic within North America, 1994) to 11.7% (for traffic from North America to Europe, 1995).

Measurement Studies of Reordering in the Internet

Mice and elephants

Colloquially, "mice" are short web transfers, and "elephants" are long-lived connections or sessions. Several measurement studies have shown that, while most of the connections represented in a trace are mice, most of the bytes or packets in a trace generally come from the elephants.

• From Figure 9 of Wide-Area Traffic: The Failure of Poisson Modeling by Paxson and Floyd, 1995, FTPDATA connections within a session are clustered into bursts, and in one trace, half of the FTP traffic volume in bytes comes from the largest 0.5% of the bursts. The traces are from LBL, UCB, DEC, and UK, from 1994, 1989, 1995, and 1991 respectively. In all of these traces, the largest 2% of the bursts account for at least half of the bytes.

• For the 1995 dataset of web client workloads discussed in Changes in Web Client Access Patterns: Characteristics and Caching Implications by Barford et al., the largest 1% of the files accounted for over half of the bytes transferred. In the 1998 dataset, the largest 5% of the files accounted for half of the bytes transferred.

• From Figure 2A in Load-Sensitive Routing of Long-Lived IP Flows by Shaikh, Rexford, and Shin, 1999, of the port-to-port flows in the ISP traffic trace, more than 85% of the packets are from the roughly 20% of the flows that have more than 10 packets. More than 50% of the packets are from the less than 2% of the flows that have more than 130 packets.

• In a July 2000 trace of wide-area traffic to and from UC Berkeley, while half the flows were at most four packets long, only 10% of the bytes were from flows of 10 packets or less; only 25% of the bytes were from flows of 100 packets or less; and 50% of the bytes were from flows of 650 packets or less. [Ratul Mahajan]

• We are aware of only one trace that is dominated by mice rather than by elephants. Vern Paxson reports that for an October 1998 trace of traffic to and from a Yahoo image server, more than half of the packets were from flows of at most twelve packets.

• The Self-Similarity and Long Range Dependence in Networks page lists references on heavy-tailed distributions in network traffic.

Traffic measurements using global routing data

• Cowie, J., Ogielski, A., Premore, B., and Yuan, Y., Global Routing Instabilities during Code Red II and Nimda Worm Propagation. Preliminary report on strong correlations between BGP message storms and propagation periods for Microsoft worms such as Code Red and Nimda.
  ``What were thought to be purely traffic-based denials of service in fact are seen to generate widespread end-to-end routing instability originating at the Internet's edge.''

Congestion and Topology

• A. Akella, S. Seshan, and A. Shaikh, An Empirical Evaluation of Wide-Area Internet Bottlenecks, 2003.
  Conventional wisdom has been that the performance limitations in the current Internet lie at the edges of the network i.e last mile connectivity to users, or access links of stub ASes. As these links are upgraded, however, it is important to consider where new bottlenecks and hot-spots are likely to arise."

Tools and infrastructures for measurement and analysis

• CAIDA's Measurement Tool Taxonomy lists measurement and analysis tools as well as measurement and analysis infrastructures that could help answer the congestion-control questions discussed here.

• Network Monitoring Tools from Les Cottrell's web pages.

• Interesting web sites for Internet Monitoring from Les Cottrell's web pages.

• CAIDA's Beluga tool provides a real-time graph of RTTS and packet loss to a host.