John S. Otto, Mario A. Sanchez, David R. Choffnes*, Fabián E. Bustamante, Georgos Siganos** Northwestern, EECS * U.

Slides:



Advertisements
Similar presentations
Measuring the Deployment of IPv6: Topology, Routing, and Performance Amogh Dhamdhere, Matthew Luckie, Bradley Huffaker, kc claffy (CAIDA / UC San Diego)
Advertisements

Clayton Sullivan PEER-TO-PEER NETWORKS. INTRODUCTION What is a Peer-To-Peer Network A Peer Application Overlay Network Network Architecture and System.
CSE534- Fundamentals of Computer Networking Lecture 12-13: Internet Connectivity + IXPs (The Underbelly of the Internet) Based on slides by D. Choffnes.
CS 4700 / CS 5700 Network Fundamentals Lecture 16: IXPs (The Underbelly of the Internet) Revised 3/23/2015.
On the Effectiveness of Measurement Reuse for Performance-Based Detouring David Choffnes Fabian Bustamante Fabian Bustamante Northwestern University INFOCOM.
Ten Years in the Evolution of the Internet Ecosystem
Measurement, Modeling, and Analysis of a Peer-2-Peer File-Sharing Workload Presented For Cs294-4 Fall 2003 By Jon Hess.
Streaming Video Traffic: Characterization and Network Impact Kobus van der Merwe Shubho Sen Chuck Kalmanek
TELECOM ITALIA GROUP Ongoing Activities Report BT London, Feb 15, 2011.
Shifting Demographics: Mapping the World Population
University of Nevada, Reno Ten Years in the Evolution of the Internet Ecosystem Paper written by: Amogh Dhamdhere, Constantine Dovrolis School of Computer.
Mohamed Hefeeda 1 School of Computing Science Simon Fraser University, Canada ISP-Friendly Peer Matching without ISP Collaboration Mohamed Hefeeda (Joint.
IPlane: An Information Plane for Distributed Services Offence by: Anup Goyal Sagar Vemuri.
An Analysis of Internet Content Delivery Systems Stefan Saroiu, Krishna P. Gommadi, Richard J. Dunn, Steven D. Gribble, and Henry M. Levy Proceedings of.
Structure of the Internet Update for 1 st H/Wk We will start lab next week Paper presentation at the end of the session Next Class MPLS.
End-to-End Issues. Route Diversity  Load balancing o Per packet splitting o Per flow splitting  Spill over  Route change o Failure o policy  Route.
Tradeoffs in CDN Designs for Throughput Oriented Traffic Minlan Yu University of Southern California 1 Joint work with Wenjie Jiang, Haoyuan Li, and Ion.
Internet Inter-Domain Traffic Craig Labovitz, Scott Iekel-Johnson, Danny McPherson, Jon Oberheide, Farnam Jahanian Presented by: Kaushik Choudhary.
Can Internet Video-on-Demand Be Profitable? SIGCOMM 2007 Cheng Huang (Microsoft Research), Jin Li (Microsoft Research), Keith W. Ross (Polytechnic University)
Differences between In- and Outbound Internet Backbone Traffic Wolfgang John and Sven Tafvelin Dept. of Computer Science and Engineering Chalmers University.
Ao-Jan Su, David R. Choffnes, Fabián E. Bustamante and Aleksandar Kuzmanovic Department of EECS Northwestern University Relative Network Positioning via.
Internet Policy Day 1 - Workshop Session No. 2 Market structure Prepared for CTO by Link Centre, Witwatersrand University, South Africa.
Taming the Torrent: A Practical Approach to Reducing Cross-ISP Traffic in Peer-to-Peer Systems David R. Choffnes and Fabián E. Bustamante Speaker: Wally.
Global Lesson Social Studies On-line Continents Second Grade Social Studies On-line Continents Second Grade.
P4P: Provider Portal for Applications Haiyong Xie, Y. Richard Yang Arvind Krishnamurthy, Yanbin Liu, Avi Silberschatz SIGCOMM ’08 Hoon-gyu Choi
CPSC 441: Multimedia Networking1 Outline r Scalable Streaming Techniques r Content Distribution Networks.
David Choffnes Fabián Bustamante Zihui Ge Northwestern University* Northwestern University AT&T Labs *currently at U.
Media &Content: In Strictest Confidence. BT Operate © British Telecommunications plc 2 Agenda 1.Introductions 2.Performance to date 3.Growth Plans 4.New.
Aditya Akella The Performance Benefits of Multihoming Aditya Akella CMU With Bruce Maggs, Srini Seshan, Anees Shaikh and Ramesh Sitaraman.
TDTS21: Advanced Networking Lecture 7: Internet topology Based on slides from P. Gill and D. Choffnes Revised 2015 by N. Carlsson.
FOREIGN MARKET SHARE STATISTICS ON INBOUND INTERNATIONAL TOURISM 1.
Aemen Lodhi (Georgia Tech) Amogh Dhamdhere (CAIDA)
April 4th, 2002George Wai Wong1 Deriving IP Traffic Demands for an ISP Backbone Network Prepared for EECE565 – Data Communications.
Can ISPs be Profitable Without Violating Network Neutrality? Amogh Dhamdhere Constantine Dovrolis Georgia Tech.
CSE534- Fundamentals of Computer Networking Lecture 12-13: Internet Connectivity + IXPs (The Underbelly of the Internet) Based on slides by D. Choffnes.
정하경 MMLAB Fundamentals of Internet Measurement: a Tutorial Nevil Brownlee, Chris Lossley, “Fundamentals of Internet Measurement: a Tutorial,” CMG journal.
Ming-Chen Zhao, Paarijaat Aditya, Yin Lin Andreas Haeberlen, Peter Druschel, Bruce Maggs, and William Wishon A First Look at a Hybrid Content Delivery.
Performance Limitations of ADSL Users: A Case Study Matti Siekkinen, University of Oslo Denis Collange, France Télécom R&D Guillaume Urvoy-Keller, Ernst.
09/13/04 CDA 6506 Network Architecture and Client/Server Computing Peer-to-Peer Computing and Content Distribution Networks by Zornitza Genova Prodanoff.
Video Content Networking Does it Scale? GPF 2.0 March 2007 Martin J. Levy– Moderator Patrick Gilmore– Akamai Brokaw Price– Yahoo Guy Tal– Limelight Networks.
John S. Otto Mario A. Sánchez John P. Rula Fabián E. Bustamante Northwestern, EECS.
WHAT'S THE DIFFERENCE BETWEEN A WEB APPLICATION STREAMING NETWORK AND A CDN? INSTART LOGIC.
International Internet Statistics ITU ICT Indicators Meeting February 10, 2005.
Drafting Behind Akamai (Travelocity-Based Detouring) Ao-Jan Su, David R. Choffnes, Aleksandar Kuzmanovic and Fabián E. Bustamante Department of EECS Northwestern.
Internet Strucure Internet structure: network of networks Question: given millions of access ISPs, how to connect them together? access.
Investigation of Traffic Dependencies between IXPs in Failure Scenarios APRICOT 2016, Peering Forum Auckland, New Zealand Arnold Nipper Chief.
© 2015 The SmartenIT Consortium 1 Commercial in Confidence DTM for minimization of inter-domain traffic cost Grzegorz Rzym, AGH, June 16, 2015 Socially-aware.
Office of Electronic Communications (UKE)
The Hidden Locality in Swarms
Taming the Torrent (Can’t P2P and ISPs just get along?)
P4P : Provider Portal for (P2P) Applications Haiyong Xie, Y
Parallel Autonomous Cyber Systems Monitoring and Protection
A New Model for Interconnection ECC Report 75
Interpretation of Data
THE DRC INTERNET ECOSYSTEM AND THE PEERING DEVELOPMENT
3 | Analyzing Server, Network, and Client Health
VTS Health Assessment from SMF Type 94 records for
Video Distribution on Internet
CS 4700 / CS 5700 Network Fundamentals
Interpretation of Data
Internet Interconnection
Fast Growth countries (Figures may not add to totals due to rounding) Natural Time unit Births Deaths increase Year.
AWS Cloud Computing Masaki.
Privacy-Preserving Dynamic Learning of Tor Network Traffic
Use of Simplex Satellite Configurations to support Internet Traffic
MVNO: Mobile Virtual Network Operator
Interpretation of Data
AS15169.
The Elusive Internet Flattening: 10 Years of IXP Growth
SwiNOG May 2013 Ian Cleary – Director Internet Services EMEA
Presentation transcript:

John S. Otto, Mario A. Sanchez, David R. Choffnes*, Fabián E. Bustamante, Georgos Siganos** Northwestern, EECS * U. Wash, CSE ** Telefónica Research

Otto, Sánchez, Choffnes, Bustamante & Siganos 2 A large, global peer-to-peer system Millions of users exchanging content Virtually every country in the world On Blind Mice and the Elephant

Otto, Sánchez, Choffnes, Bustamante & Siganos 3 System’s measured network impact depends on measurement vantage point –How much of network traffic is from BitTorrent? On Blind Mice and the Elephant Eastern Europe 57% (ipoque) South America 20% (ipoque) No, Germany is 9-15% (Maier et al. IMC’09) Germany 37% (ipoque)

Otto, Sánchez, Choffnes, Bustamante & Siganos 4 A view from a broad set of end users –To sample its overall network traffic –Understand where it flows –Who pays for it (and how expensive it is) This work –Relies on end users as vantage points Captures a sample of all BitTorrent traffic Reveals traffic’s path through the network –Public view is not sufficient to map most BitTorrent traffic –ISP data provides context to understand cost of BitTorrent traffic On Blind Mice and the Elephant

Otto, Sánchez, Choffnes, Bustamante & Siganos 5 Representative sample of users –500,000 users, 3,300 networks, 169 countries Running extensions (Ono & NEWS) for Vuze BitTorrent client –Anonymously report statistics –Provide application-level data e.g. session length, per-connection transfer volumes Log 13 TB of traffic per day –Conduct active measurements to reveal traffic paths With public view alone, we can map 25% of traffic Supplemented with traceroutes, we can map 89% On Blind Mice and the Elephant

Otto, Sánchez, Choffnes, Bustamante & Siganos 6 How BitTorrent is being used –Who is using BitTorrent? –When do people run BitTorrent? –How much traffic does it generate? –Study data from Nov to Nov Where the generated traffic flows Who pays for it and how much On Blind Mice and the Elephant

Otto, Sánchez, Choffnes, Bustamante & Siganos 7 On Blind Mice and the Elephant Decrease in Europe Increase in Asia, Africa and Oceania Connected peers by continent Overall population reduced by 10% Locations of users change over time

Otto, Sánchez, Choffnes, Bustamante & Siganos 8 On Blind Mice and the Elephant Rate of growth of connected users per continent relative to Nov Europe continues to drop N. America, S. America remain stable since % growth in Africa and 47% in Asia

Otto, Sánchez, Choffnes, Bustamante & Siganos 9 Shift away from overnight use Peak usage aligns with evening hours, local time –Potential impact on ISPs’ costs under burstable billing On Blind Mice and the Elephant European peers seen on weekdays Normalized number of peers seen per hour in Europe, depending on time of day

Otto, Sánchez, Choffnes, Bustamante & Siganos 10 25% increase in per-peer hourly download volume Despite a 20% drop in total connections, a 12% increase in overall system traffic On Blind Mice and the Elephant Per-peer hourly download volume (in MB) over the last year

Otto, Sánchez, Choffnes, Bustamante & Siganos 11 Overall population reduced by 10% –But large increase in Africa and Asia Peak usage aligns with evening hours 12% increase in overall system traffic –25% increase in per-peer hourly download volume So where’s the traffic? On Blind Mice and the Elephant

Otto, Sánchez, Choffnes, Bustamante & Siganos 12 How “deep” does traffic go in the network? Who is paying for it? Traffic path analysis to see which networks carry most BitTorrent traffic –Tier 1: Well-known networks –Tier 2: Large transit providers –Tier 3: Small transit providers –Tier 4: Content/access/hosting providers Enterprise customers On Blind Mice and the Elephant Tiers based on Dhamdhere and Dovrolis, IMC 2008

Otto, Sánchez, Choffnes, Bustamante & Siganos 13 Most traffic stays at or below Tier 3 Significant fraction of traffic never reaches Tiers 1 or 2 –Typically missed by in-network monitoring studies from the core On Blind Mice and the Elephant Fraction of each peer’s traffic that reaches Tier X Smaller fraction of traffic

Otto, Sánchez, Choffnes, Bustamante & Siganos 14 Traffic generally stays in the originating tier Tier 2 networks do not provide “intermediate” level of connectivity between Tiers 1 & 3 On Blind Mice and the Elephant Traffic from Tier 2 to Tier 2Traffic from Tier 3 to Tier 3

Otto, Sánchez, Choffnes, Bustamante & Siganos 15 How BitTorrent is being used Where the generated traffic flows –Most traffic is handled at or below Tier 3 Who pays for it and how much On Blind Mice and the Elephant

Otto, Sánchez, Choffnes, Bustamante & Siganos 16 Determine BitTorrent cost relative to other traffic –ISP X’s data provides context to interpret traffic sample Study at granularity of individual network links Consider common burstable billing model –e.g. 95 th -percentile billing Data for several of ISP X’s links over 1 week On Blind Mice and the Elephant Providers Customers

Otto, Sánchez, Choffnes, Bustamante & Siganos 17 Aggregate link volume for each 5 minute bin Cost is based on 95 th -percentile bin’s value Under burstable billing model, not all bytes may have the same cost –Peak-hour bytes are more expensive than off-peak On Blind Mice and the Elephant 95 th -percentile value When value is defined All Traffic

Otto, Sánchez, Choffnes, Bustamante & Siganos 18 On Blind Mice and the Elephant Other BT Other BT BitTorrent at peak hour is more expensive Use Shapley value to determine relative cost of BitTorrent –Shapley value gives the cost contribution of BitTorrent traffic –Compare to other traffic on the network –Is BitTorrent’s cost more than its “fair share” by volume? BitTorrent peaks at 3AMBitTorrent peaks at 9PM BitTorrent’s contribution to cost BT Other

Otto, Sánchez, Choffnes, Bustamante & Siganos 19 On Blind Mice and the Elephant BitTorrent traffic is generally more expensive than other traffic What traffic characteristics result in high relative cost? Additional cost of BitTorrent traffic, percent above relative cost of 1

Otto, Sánchez, Choffnes, Bustamante & Siganos 20 High relative cost of BitTorrent –Large coefficient of variation (“C.V.”, size of peaks in BitTorrent traffic) –Small cross-correlation offset (“X-corr”, alignment with overall traffic) On Blind Mice and the Elephant Out-of-phase peaksAligned peaks Small peaks Large peaks

Otto, Sánchez, Choffnes, Bustamante & Siganos 21 High relative cost of BitTorrent –Large coefficient of variation (“C.V.”, size of peaks in BitTorrent traffic) –Small cross-correlation offset (“X-corr”, alignment with overall traffic) On Blind Mice and the Elephant Out-of-phase peaksAligned peaks ISP B X-corr: 3.2 hours C.V.: 188% Relative cost: 50% ISP A X-corr: -7.1 hours C.V.: 130% Relative cost: 13% ISP F X-corr: 7.4 C.V.: 325% Relative cost: 52% ISP E X-corr: 1.6 C.V.: 158% Relative cost: 83% Small peaks Large peaks

Otto, Sánchez, Choffnes, Bustamante & Siganos 22 BitTorrent is still alive and costly –Most traffic stays at the edge of the network –It is moving into prime-time –Logically, it is relatively more expensive A broad view from the edge of the network is required to see the system’s full usage spectrum Approach is general to understanding other distributed systems –Video streaming –Peer-to-peer CDNs On Blind Mice and the Elephant