Jin Li, Principal Researcher (Collaborators: Cheng Huang, Keith Ross) Communication and Collaboration Systems Microsoft Research 1.

Slides:



Advertisements
Similar presentations
Network Aware Forward Caching Presenter: Alexandre Gerber Jeffrey Erman, Mohammad T. Hajiaghayi, Dan Pei, Oliver Spatscheck AT&T Labs Research April 24.
Advertisements

Presentation | P2P Media Summit CacheLogic Advanced Solutions for P2P Networks Presentation by Andrew Parker, CTO
Web Streaming Solution DIGIMELD GRID-STREAMING SOLUTIONS Copyright © 2008 DigiMeld, Inc.
Abacast - Confidential1 Hybrid Content Delivery Network (CDN) Technologies and Services.
1Abacast - Confidential1 Hybrid Content Delivery Network (CDN) Technologies and Services.
1Abacast - Confidential1 Hybrid Content Delivery Network (CDN) Technologies and Services.
1 Jin Li Microsoft Research. Outline The Upcoming Video Tidal Wave Internet Infrastructure: Data Center/CDN/P2P P2P in Microsoft Locality aware P2P Conclusions.
Novasky: Cinematic-Quality VoD in a P2P Storage Cloud Speaker : 童耀民 MA1G Authors: Fangming Liu†, Shijun Shen§,Bo Li†, Baochun Li‡, Hao Yin§,
Clayton Sullivan PEER-TO-PEER NETWORKS. INTRODUCTION What is a Peer-To-Peer Network A Peer Application Overlay Network Network Architecture and System.
CONFIDENTIAL©2008 MEDIAMELON, INC. DCIA PRESENTATION Kumar Subramanian
Using P2P Technologies for Video on Demand (VoD) Limor Gavish limorgav at tau.ac.il Yuval Meir wil at tau.ac.il Tel-Aviv University Based on:  Cheng Huang,
Kangaroo: Video Seeking in P2P Systems Xiaoyuan Yang †, Minas Gjoka ¶, Parminder Chhabra †, Athina Markopoulou ¶, Pablo Rodriguez † † Telefonica Research.
Netflix Content Delivery RIPE – April 2012 – David Temkin 1.
Can Internet Video-On-Demand be Profitable? Jiwon Park July 11,2012.
Akamai networks,48000 servers and 70 countries in the world.
Cloud Download : Using Cloud Utilities to Achieve High-quality Content Distribution for Unpopular Videos Yan Huang, Tencent Research, Shanghai, China Zhenhua.
Streaming Video Traffic: Characterization and Network Impact Kobus van der Merwe Shubho Sen Chuck Kalmanek
1 Content Delivery Networks iBAND2 May 24, 1999 Dave Farber CTO Sandpiper Networks, Inc.
19 Historical overview Main challenge: How to distribute content in high quality over the Internet cost-effectively? • Traditional “Best-effort” model:
Mohamed Hefeeda 1 School of Computing Science Simon Fraser University, Canada ISP-Friendly Peer Matching without ISP Collaboration Mohamed Hefeeda (Joint.
P2P 2.0 and it’s impact on the Internet
CS 898N – Advanced World Wide Web Technologies Lecture 2: Overview of the Internet Chin-Chih Chang
1 Chapter 9 The Internet in Business: Corporations, Businesses, and Entrepreneurs.
End-to-End Analysis of Distributed Video-on-Demand Systems Padmavathi Mundur, Robert Simon, and Arun K. Sood IEEE Transactions on Multimedia, February.
An Analysis of Internet Content Delivery Systems Stefan Saroiu, Krishna P. Gommadi, Richard J. Dunn, Steven D. Gribble, and Henry M. Levy Proceedings of.
1 A Framework for Lazy Replication in P2P VoD Bin Cheng 1, Lex Stein 2, Hai Jin 1, Zheng Zhang 2 1 Huazhong University of Science & Technology (HUST) 2.
1 Can Internet Video-on-Demand be Profitable? Cheng Huang, Jin Li (Microsoft Research Redmond), Keith W. Ross (Polytechnic University) ACM SIGCOMM 2007.
Periodic broadcasting with VBR-encoded video Despina Saparilla, Keith W. Ross, and Martin Reisslein 1999 IEEE INFOCOM Hsin-Hua, Lee.
An Overlay Multicast Infrastructure for Live/Stored Video Streaming Visual Communication Laboratory Department of Computer Science National Tsing Hua University.
Semester 4 - Chapter 3 – WAN Design Routers within WANs are connection points of a network. Routers determine the most appropriate route or path through.
On-Demand Media Streaming Over the Internet Mohamed M. Hefeeda, Bharat K. Bhargava Presented by Sam Distributed Computing Systems, FTDCS Proceedings.
Some recent work on P2P content distribution Based on joint work with Yan Huang (PPLive), YP Zhou, Tom Fu, John Lui (CUHK) August 2008 Dah Ming Chiu Chinese.
Tradeoffs in CDN Designs for Throughput Oriented Traffic Minlan Yu University of Southern California 1 Joint work with Wenjie Jiang, Haoyuan Li, and Ion.
Can Internet Video-on-Demand Be Profitable? SIGCOMM 2007 Cheng Huang (Microsoft Research), Jin Li (Microsoft Research), Keith W. Ross (Polytechnic University)
1 Proxy-Assisted Techniques for Delivering Continuous Multimedia Streams Lixin Gao, Zhi-Li Zhang, and Don Towsley.
Welcome Thank you for joining us today. Please stand by while we wait for more attendees to join in. The webcast will begin momentarily.
Distributing Content Simplifies ISP Traffic Engineering Abhigyan Sharma* Arun Venkataramani* Ramesh Sitaraman*~ *University of Massachusetts Amherst ~Akamai.
Page 18/25/2015 CSE 40373/60373: Multimedia Systems CSE 4/60373: Multimedia Systems  Outline for today  32: Y.-F. Chen, Y. Huang, R. Jana, H. Jiang,
Information Systems Today: Managing in the Digital World TB4-1 4 Technology Briefing Networking.
COnvergence of fixed and Mobile BrOadband access/aggregation networks Work programme topic: ICT Future Networks Type of project: Large scale integrating.
Kendra initiative CONTENT DELIVERY RESEARCH Content Delivery Summit Amsterdam February 2001 "Fueling the demand for broadband Internet" Daniel Harris -
Can Internet VoD be Profitable? Cheng Huang (MSR), Jin Li (MSR), Keith W. Ross (NY Polytechnique)
RSC Part I: Introduction Redes y Servicios de Comunicaciones Universidad Carlos III de Madrid These slides are, mainly, part of the companion slides to.
Chapter 4. After completion of this chapter, you should be able to: Explain “what is the Internet? And how we connect to the Internet using an ISP. Explain.
1 Towards Cinematic Internet Video-on-Demand Bin Cheng, Lex Stein, Hai Jin and Zheng Zhang HUST and MSRA Huazhong University of Science & Technology Microsoft.
Kendra initiative CONTENT DELIVERY RESEARCH New Broadband Content Delivery Strategies London - September 2001 "Fueling the demand for broadband Internet"
2: Application Layer1 Chapter 2 outline r 2.1 Principles of app layer protocols r 2.2 Web and HTTP r 2.3 FTP r 2.4 Electronic Mail r 2.5 DNS r 2.6 Socket.
Department of Information Engineering The Chinese University of Hong Kong A Framework for Monitoring and Measuring a Large-Scale Distributed System in.
1 On the Placement of Web Server Replicas Lili Qiu, Microsoft Research Venkata N. Padmanabhan, Microsoft Research Geoffrey M. Voelker, UCSD IEEE INFOCOM’2001,
1 MIKE NIELSEN DIRECTOR SP MARKETING. CONTENT DELIVERY NETWORKS.
1 On the Placement of Web Server Replicas Lili Qiu, Microsoft Research Venkata N. Padmanabhan, Microsoft Research Geoffrey M. Voelker, UCSD IEEE INFOCOM’2001,
Kiew-Hong Chua a.k.a Francis Computer Network Presentation 12/5/00.
Internet Protocol TeleVision
CS Spring 2009 CS 414 – Multimedia Systems Design Lecture 37 – P2P Applications/PPLive Klara Nahrstedt Spring 2009.
PROP: A Scalable and Reliable P2P Assisted Proxy Streaming System Computer Science Department College of William and Mary Lei Guo, Songqing Chen, and Xiaodong.
SocialTube: P2P-assisted Video Sharing in Online Social Networks
Can Internet Video-on-Demand Be Profitable? Cheng Huang, Jin Li (Microsoft Research), Keith W. Ross (Polytechnic University) ACM SIGCOMM 2007.
Advanced Network Seminar P2P in VoD Constantin Radchenko.
Bruce Maggs Duke University Akamai Technologies Carnegie Mellon University delivering content to the next billion.
ADVANCED COMPUTER NETWORKS Peer-Peer (P2P) Networks 1.
Ming-Chen Zhao, Paarijaat Aditya, Yin Lin Andreas Haeberlen, Peter Druschel, Bruce Maggs, and William Wishon A First Look at a Hybrid Content Delivery.
09/13/04 CDA 6506 Network Architecture and Client/Server Computing Peer-to-Peer Computing and Content Distribution Networks by Zornitza Genova Prodanoff.
TV Broadcasting What to look for Architecture TV Broadcasting Solution
Semester 4 - Chapter 3 – WAN Design
LECTURE 34: WEB PROGRAMMING FOR SCALE
LECTURE 32: WEB PROGRAMMING FOR SCALE
LECTURE 33: WEB PROGRAMMING FOR SCALE
Who We Are – Brief History
Challenges with developing a Commercial P2P System
LECTURE 33: WEB PROGRAMMING FOR SCALE
Presentation transcript:

Jin Li, Principal Researcher (Collaborators: Cheng Huang, Keith Ross) Communication and Collaboration Systems Microsoft Research 1

2 Introduction: Internet Video on the Rise

Internet Video is on the Rise Video streams served increased 38.8% in 2006 to billion (Source: AccuStream iMedia Research) 53 web-video startup in 2006 (US), $521M VC funding (Source: DowJones VentureOne) Major studio goes into Web Video $410M video ads revenue in 2006 and grow by 89% in 2007 (0.6% of $74B TV ad market, Internet ads $16.4B in 2006, expect to grow 19% in 2007) [source: Emarketer] 3

Internet Video is Growing: in Popularity & Quality 4 Apr. 2006Dec. 2006Up (%) # of views (million) # of users (million) video quality evolution popularity evolution

5 Internet Video Delivery: Data Center vs. CDN vs. P2P

Just Build More Powerful Data Center? 6

Data Center Capacity VHS quality video streaming: 500 kbps (H.264) 200,000 viewers = 100 Gbps Data center capacity: Tera Grid (UIUC) 30 petabyte of storage 40 Gbps backbone: 80k video viewers 7

CDN Is Not The Answer 8 Akamai 20,000 servers, 900 point of presence, 71 countries 400Gbps bandwidth Network optimized for latency Limelight 25 point of presence, hundreds servers per presence 1,000Gbps bandwidth Akamai+Limelight: 2.8 million viewers. Current TV audience Olympics: 2.5 billion viewers Each viewer may have his/her own interest (different sport event, athlete nationality, etc.)

Peer Assisted Delivery is the Way To Scale 9 Economical to run Saves server/CDN bandwidth, disk I/O, CPU, memory Robust no single point of failure in network Super-scalable system capacity increases with number of nodes peer resource bandwidth CPU memory hard drive

P2P Benefit Consumers: Better Video Quality, More Selection 10

11 Case Study 1: On Demand Internet Video

Peer Assisted Delivery: Mode File Sharing broadcast On Demand Streaming (Interactive TV) Live Messenger FolderShare Groove 12

Peer Buffer Map: File Sharing 13 Peer 1 Peer 2 Peer 3 Peer 4 Peer 5 Peer 6

Peer Buffer Map: Broadcast 14 Peer 1 Peer 2 Peer 3 Peer 4 Peer 5 Peer 6

Peer Buffer Map: On Demand 15 Peer 1 Peer 2 Peer 3 Peer 4 Peer 5 Peer 6

MSN VoD Service 16 Traces from the on-demand service of MSN Video 9-month period: Apr. – Dec M streaming requests 59,000 unique videos

Peer-assisted VoD Model 17 Guaranteed QoS: always available server Performance metric: server bandwidth Peers upload what / when they are watching conservative assumption servers in data centers/CDN

Peer Bandwidth Download BW is measured by Windows Media Server no accurate measurement beyond 3.5Mbps Upload BW is inferred Average upload: 500+ kbps 18 DSL2 Cable Ethernet Modem ISDN DSL1

Bandwidth Allocation Policies 19 Assumptions peers always start watching from beginning VoD: earlier peers upload to later peers 1 st policy: no-prefetching only satisfy demand for smooth playback, do not further build up the buffer used by commercial live streaming companies to offer VoD servers in data centers arrival ask ask server ask ask server 3 2 1

Bandwidth allocation policies (2) 20 Prefetching – to utilize remaining upload capacity 2 nd policy: water-leveling 3 rd policy: greedy Lower bound allow later peers upload to earlier ones no arrival order constraints servers in data centers arrival water-leveling: greedy: water-leveling: greedy: 4 2

Observations on Policies (Simulated: Peer Poisson Arrival) Prefetching is crucial “free” to increase video bitrate “balanced mode” is most difficult S ≈ D Greedy policy works best lowest server load very close to bound more available upload

Server BW Reduction – Two Videos select top two most popular videos ~800,000 views during April, 2006 significant server bandwidth reduction using peer assistance less server BW even increase quality 3 times bitrate) 22 gold streamsilver stream

Server BW reduction – two videos select top two most popular videos ~800,000 views during April, 2006 significant server bandwidth reduction using peer assistance less server BW even increase quality 3 times bitrate) 23 gold streamsilver stream

Server BW reduction – all videos 24 12,000+ videos server bandwidth reduction in all categories 1.23Gbps  36.9Mbps (97%) 1.23Gbps  bitrate (38%) April 2006

25 Locality Aware P2P Delivery

P2P Traffic Today to present: fueled by Napster, KaZaA, eDonkey and BitTorrent CacheLogic Research Internet Protocol Breakdown

Internet Traffic on the Rise 27 Internet traffic trend: grow at a compound monthly average of 7.4% in 2006 Internet traffic doubles per year Traffic at Amsterdam Internet Exchange (AMS-IX)

Locality to the Rescue 28 Internet Hierarchy AS ISP POP Home/corporation Branch office of a corporation Delivery content in a locality aware fashion Beyond ISP aware delivery

Internet : Grand View 29

Impact on ISPs 30 Tier 1 ISP Tier 2 ISP AS sibling peering peering entity boundary sibling entity boundary transit Tier 2 ISP AS  Economics of ISP relationships  sibling relationship several ISPs belong to same org  peering relationship mutual beneficial free agreement (to certain extent)  transit relationship one ISP pays another

Inside ISP 31

ISP POP (Point of Presence) 32

Inside Home/Branch Office 33 neighborhood homecorporation Branch office

Identify Peers Locality 34 Information used External IP address Internal IP address Subnet mask Peer locality ISP (AS) ISP POP Home/corporation Corporate branch office Peers are considered closer if they are in a smaller common neighborhood

MAP External IP Address to AS 35 Using BGP dump

Identify POP 36 POP neighborhood Identify one peer that is directly connected to the Internet at some point of time Collect its external IP address and the subnet mask Infer the subnet neighborhood where other peers belong, even if they are not directly connected to the Internet

Below POP 37 Home/corporation neighborhood All peers with the same external IP address Corporation branch office All peers with the same external IP address, and on the same internal subnet (based on subnet mask)

Locality Aware Topology Building 38 Preferentially link peers within the same ISP neighborhood Say if we need to establish 20 connections We assign 50% of links to be within branch office neighborhood If there are less peers than the allocated links, we simply put the unused links back to the pool We then assign 50% of unused links to be within home/office neighborhood The next 50% of unused links are assigned within POP neighborhood The next 50% of unused links are assigned within AS neighborhood The rest of the links are used for cross-AS connections

Example 39 ScenarioNeighborhoodBranch officeHome/ corporation ISPASOutside AS 1 Total peers Connected peers Total peers Connected peers Total peers Connected peers02099

Locality Aware P2P Scheduling 40 Preferentially deliver content to peers within closer neighborhood Propagate neighborhood availability information Exchange with a outside peer preferentially content that is not available in the neighborhood

Preliminary Result: ISP Friendly Without ISP-friendly Much more cross sibling than peering boundary Significant crossing boundary traffic 41 Without ISP-friendly

Preliminary Result: ISP Friendly Pure ISP-friendly 1 video  separate distributions still surprising reductions but unnecessarily conservative ISP could help by sharing information 42 svr rate (Mbps) no P2P sibling partition peering partition silver top cut cross boundary traffic completely

43 Conclusions

Conclusion 44 Peer assisted delivery is the way to go for mass content delivery over the world Peer assistance can significantly reduce server bandwidth requirement Demonstrated in real world for file sharing & broadcast Shown in our work for on demand streaming Locality aware P2P delivery is the way to scale