P4P: Towards Cooperation between P2P and ISPs Haiyong Xie (Yale) Arvind Krishnamurthy (U. Washington) Avi Silberschatz (Yale) Y. Richard Yang (Yale) 2007-7-25.

Slides:



Advertisements
Similar presentations
P4P: ISPs and P2P Laird Popkin, Pando Networks Doug Pasko, Verizon.
Advertisements

P4P Working Group Doug Pasko, Co-Chair, Verizon
P4P meeting Eitan Efron, VP BD January 2008.
Optimal Capacity Sharing of Networks with Multiple Overlays Zheng Ma, Jiang Chen, Yang Richard Yang and Arvind Krishnamurthy Yale University University.
Ningning HuCarnegie Mellon University1 Optimizing Network Performance In Replicated Hosting Peter Steenkiste (CMU) with Ningning Hu (CMU), Oliver Spatscheck.
Phalanx: Withstanding Multimillion-Node Botnets Colin Dixon Arvind Krishnamurthy Tom Anderson University of Washington NSDI 2008.
Multi-Layer Switching Layers 1, 2, and 3. Cisco Hierarchical Model Access Layer –Workgroup –Access layer aggregation and L3/L4 services Distribution Layer.
Receiver-driven Layered Multicast S. McCanne, V. Jacobsen and M. Vetterli University of Calif, Berkeley and Lawrence Berkeley National Laboratory SIGCOMM.
On Selfish Routing In Internet-like Environments Lili Qiu (Microsoft Research) Yang Richard Yang (Yale University) Yin Zhang (AT&T Labs – Research) Scott.
Congestion Control An Overview -Jyothi Guntaka. Congestion  What is congestion ?  The aggregate demand for network resources exceeds the available capacity.
Receiver-driven Layered Multicast S. McCanne, V. Jacobsen and M. Vetterli SIGCOMM 1996.
CStream: Neighborhood Bandwidth Aggregation For Better Video Streaming Thangam Vedagiri Seenivasan Advisor: Mark Claypool Reader: Robert Kinicki 1 M.S.
Mohamed Hefeeda 1 School of Computing Science Simon Fraser University, Canada ISP-Friendly Peer Matching without ISP Collaboration Mohamed Hefeeda (Joint.
Chien-Hao Chien, Shun-Yun Hu, Jehn-Ruey Jiang Adaptive Computing and Networking (ACN) Laboratory Department of Computer Science and Information Engineering.
A Comparison of Layering and Stream Replication Video Multicast Schemes Taehyun Kim and Mostafa H. Ammar.
Traffic Engineering With Traditional IP Routing Protocols
Network Coding for Large Scale Content Distribution Christos Gkantsidis Georgia Institute of Technology Pablo Rodriguez Microsoft Research IEEE INFOCOM.
Improving ISP Locality in BitTorrent Traffic via Biased Neighbor Selection Ruchir Bindal, Pei Cao, William Chan Stanford University Jan Medved, George.
Shadow Configurations: A Network Management Primitive Richard Alimi, Ye Wang, Y. Richard Yang Laboratory of Networked Systems Yale University.
An Overlay Data Plane for PlanetLab Andy Bavier, Mark Huang, and Larry Peterson Princeton University.
1 CAPS: A Peer Data Sharing System for Load Mitigation in Cellular Data Networks Young-Bae Ko, Kang-Won Lee, Thyaga Nandagopal Presentation by Tony Sung,
Shadow Configurations: A Network Management Primitive Richard Alimi, Ye Wang, and Y. Richard Yang Laboratory of Networked Systems Yale University February.
Kyushu University Graduate School of Information Science and Electrical Engineering Department of Advanced Information Technology Supervisor: Professor.
1 P4P: Provider Portal for Applications Haiyong Xie( 謝海永 )† Y. Richard Yang† *Arvind Krishnamurthy Yanbin Liu§ Avi Silberschatz† †Yale University *University.
P4P: Proactive Provider Assistance for P2P Haiyong Xie (Yale) *This is a joint work with Arvind Krishnamurthy (UWashington) and Richard.
On Self Adaptive Routing in Dynamic Environments -- A probabilistic routing scheme Haiyong Xie, Lili Qiu, Yang Richard Yang and Yin Yale, MR and.
Building a Strong Foundation for a Future Internet Jennifer Rexford ’91 Computer Science Department (and Electrical Engineering and the Center for IT Policy)
Tradeoffs in CDN Designs for Throughput Oriented Traffic Minlan Yu University of Southern California 1 Joint work with Wenjie Jiang, Haoyuan Li, and Ion.
P4P : Provider Portal for (P2P) Applications Y. Richard Yang Laboratory of Networked Systems Yale University Sept. 25, 2008 STIET Research Seminar.
Distributing Content Simplifies ISP Traffic Engineering Abhigyan Sharma* Arun Venkataramani* Ramesh Sitaraman*~ *University of Massachusetts Amherst ~Akamai.
A User Experience-based Cloud Service Redeployment Mechanism KANG Yu.
1 Proceeding the Second Exercises on Computer and Systems Engineering Professor OKAMURA Laboratory. Othman Othman M.M.
COCONET: Co-Operative Cache driven Overlay NETwork for p2p VoD streaming Abhishek Bhattacharya, Zhenyu Yang & Deng Pan.
Advanced Network Architecture Research Group 2001/11/149 th International Conference on Network Protocols Scalable Socket Buffer Tuning for High-Performance.
BitTorrent Under a Microscope: Towards Static QoS Provision in Dynamic Peer-to-Peer Networks Tom H. Luan*, Xuemin (Sherman) Shen* and Danny H. K. Tsang.
DaVinci: Dynamically Adaptive Virtual Networks for a Customized Internet Jennifer Rexford Princeton University With Jiayue He, Rui Zhang-Shen, Ying Li,
CS An Overlay Routing Scheme For Moving Large Files Su Zhang Kai Xu.
Approximate Load Balance Based on ID/Locator Split Routing Architecture 1 Sanqi Zhou, Jia Chen, Hongbin Luo, Hongke Zhang Beijing JiaoTong University
P4P : Provider Portal for (P2P) Applications Laboratory of Networked Systems Yale University.
1 BitHoc: BitTorrent for wireless ad hoc networks Jointly with: Chadi Barakat Jayeoung Choi Anwar Al Hamra Thierry Turletti EPI PLANETE 28/02/2008 MAESTRO/PLANETE.
MPLS and Traffic Engineering Ji-Hoon Yun Computer Communications and Switching Systems Lab.
Module 4: Designing Routing and Switching Requirements.
P4P: Provider Portal for Applications Haiyong Xie, Y. Richard Yang Arvind Krishnamurthy, Yanbin Liu, Avi Silberschatz SIGCOMM ’08 Hoon-gyu Choi
Software-defined Networking Capabilities, Needs in GENI for VMLab ( Prasad Calyam; Sudharsan Rajagopalan;
Higashino Lab. Maximizing User Gain in Multi-flow Multicast Streaming on Overlay Networks Y.Nakamura, H.Yamaguchi and T.Higashino Graduate School of Information.
P2P Traffic Localization by Alias Tracker for Tracker-based P2P applications (ATTP) draft-zhang-alto-attp-02 Yunfei Zhang China Mobile.
Univ. of TehranAdv. topics in Computer Network1 Advanced topics in Computer Networks University of Tehran Dept. of EE and Computer Engineering By: Dr.
HUAWEI TECHNOLOGIES CO., LTD. Page 1 Survey of P2P Streaming HUAWEI TECHNOLOGIES CO., LTD. Ning Zong, Johnson Jiang.
1 P4P - Provider Portal for Applications Based On The Article Haiyong Xie, Y. Richard Yang, Arvind Krishnamurthy, Yanbin Liu and Avi Silberschatz, P4P:
Othman Othman M.M., Koji Okamura Kyushu University 1.
P4P : Provider Portal for (P2P) Applications Y. Richard Yang Laboratory of Networked Systems Yale University Version: May 9, 2008.
P4P : Provider Portal for (P2P) Applications Laird Popkin Pando Networks, Inc Haiyong Xie Laboratory of Networked Systems Yale University.
A Utility-based Approach to Scheduling Multimedia Streams in P2P Systems Fang Chen Computer Science Dept. University of California, Riverside
6 December On Selfish Routing in Internet-like Environments paper by Lili Qiu, Yang Richard Yang, Yin Zhang, Scott Shenker presentation by Ed Spitznagel.
July 12th 1999Kits Workshop 1 Active Networking at Washington University Dan Decasper.
On Reducing Mesh Delay for Peer- to-Peer Live Streaming Dongni Ren, Y.-T. Hillman Li, S.-H. Gary Chan Department of Computer Science and Engineering The.
Proposal of OmniRAN architecture for Data Offload Service through Wireless P2P Networks Document Number: omniran Date Submitted:
P4P : Provider Portal for (P2P) Applications Haiyong Xie, Y. Richard Yang, Arvind Krishnamurthy, and Avi Silberschatz.
P4P : Provider Portal for P2P Applications Richard Alimi, Doug Pasko, Laird Popkin, Ye Wang, Y. Richard Yang ALTO/IETF 73, November 18, 2008.
CS 6401 Overlay Networks Outline Overlay networks overview Routing overlays Resilient Overlay Networks Content Distribution Networks.
P4P : Provider Portal for (P2P) Applications Y. Richard Yang Laboratory of Networked Systems Yale University Version: May 9, 2008.
1 Traffic Engineering By Kavitha Ganapa. 2 Introduction Traffic engineering is concerned with the issue of performance evaluation and optimization of.
Internet Traffic Engineering Motivation: –The Fish problem, congested links. –Two properties of IP routing Destination based Local optimization TE: optimizing.
Multiprotocol Label Switching (MPLS) Routing algorithms provide support for performance goals – Distributed and dynamic React to congestion Load balance.
ProbeCast: MANET Admission Control via Probing Soon Y. Oh, Gustavo Marfia, and Mario Gerla Dept. of Computer Science, UCLA Los Angeles, CA 90095, USA {soonoh,
P4P: Proactive Provider Assistance for P2P Haiyong Xie Yale University.
Shadow Configurations: A Network Management Primitive
P4P : Provider Portal for (P2P) Applications Haiyong Xie, Y
P4P: ISPs and P2P Laird Popkin, Pando Networks Doug Pasko, Verizon.
P4P : Provider Portal for (P2P) Applications
Presentation transcript:

P4P: Towards Cooperation between P2P and ISPs Haiyong Xie (Yale) Arvind Krishnamurthy (U. Washington) Avi Silberschatz (Yale) Y. Richard Yang (Yale)

P4PWG July Meeting 2 P2P Content Distribution Traffic volume: up to 60-70% of Internet traffic is contributed by P2P applications [cachelogic] Traffic pattern: random peering (e.g., BitTorrents) causes traffic spread across PoPs and domains Problems  Increased network resource usage (e.g., using bandwidth of more links)  Increased network operational costs  Degraded performance to other applications

P4PWG July Meeting 3 Bandwidth Battle between ISPs and P2P The battle results in a lose-lose situation ISPs try to “manage” P2P traffic  Upgrade network infrastructure  Deploy P2P caching devices  Terminate connectivity  Rate limit P2P traffic P2P tries to evade from being captured  Uses random ports  Encrypts traffic

P4PWG July Meeting 4 Where is the Fundamental Problem? Traditional ISP application feedback/control:  Routing/traffic engineering (TE)  Rate control through congestion feedback (packet drops) Ineffective for P2P  due to highly dynamic, scattered traffic pattern caused by dynamic, unguided (network-oblivious) peer selection Objective: design a framework to enable better ISP and P2P cooperation

P4PWG July Meeting 5 Design Rationale Performance improvement  for both ISPs and P2P Scalability  support a large number of P2P users and networks in dynamic settings Privacy preservation Extensibility  Application-specific requirements  Tracker-based vs. trackerless P2P systems  Gossip among peers Incremental deploymentability ISP contribution for P2P acceleration

P4PWG July Meeting 6 The P4P Framework P4P: proactive provider participation for P2P; P2P for providers; provider portal for P2P, … Two components  Control plane iTrackers: an ISP portal for P2P and content providers Three levels:  Network status: e.g., network topology  ISP policy and guideline: e.g., traffic balance ratio for inter-AS peering links, time of day preference  ISP capabilities: e.g., QoS, CoS, ISP servers participation in content distributions  Data plane [optional] Routers on data paths provide fine-grained, ISP policy-based feedbacks, e.g., utilize TCP ECN bit or feedback fields in an overlay packet header

P4PWG July Meeting 7 P4P Control Path: Obtain Network Status/Policy An iTracker for each ISP. 1: Peer queries iTracker of local ISP to obtain network status/policy 2,3: Tracker-based: peer reports status/policy to appTracker; appTracker selects peering set considering both ISP status/policy and application requirements [4]: Trackerless: peers exchange information and make peering decisions ISP B ISP A appTracker a iTracker B iTracker A b [4] 2 3

P4PWG July Meeting 8 P4P Control Path : Request Capability ISP B 5: appTracker [content provider] requests ISP B’s participation in content distribution 6: ISP B allocates servers to accelerate content distribution 7: appTracker includes ISP B’s servers in returned peering sets to peers ISP A appTracker a iTracker B iTracker A b Note: this can be extended to handle trackerless systems, as we did in the previous slide appTracker/content provider requests ISP capabilities to accelerate content distribution.

P4PWG July Meeting 9 P4P Framework: Data Path [optional] Routers mark packets to provide faster, fine-grained feedbacks, e.g., virtual capacity to optimize multihoming cost and performance ISP BISP A a b Peers adjust traffic rates according to feedbacks

P4PWG July Meeting 10 Test Plan for P4P Measurement study with Pando (in progress) Evaluate P2P self-adaptation schemes (in progress)  Generate best practices for P2P design  Serve as comparison basis iTracker (in progress)  Network information (roughly completed)  ISP policy and guideline (in progress)  ISP capability (in progress) Data path (in progress) Evaluate P4P design with Pando and Verizon (in progress)

P4PWG July Meeting 11 Preliminary Results Simulations  Discrete-event simulation a module for modeling BitTorrent protocol a module for modeling underlying network topology and data transfer dynamics using TCP rate equation  Network topology: PoP-level AT&T and Abilene topologies  Network routing: OSPF routing Internet experiments  53 Internet2 nodes on PlanetLab  iTracker for Abilene network  Use OSPF routing to re-construct traffic load on Abilene links

P4PWG July Meeting 12 Evaluation – BitTorrent on Abilene Compared to P4P, native P2P can result in  2x download completion time  2x higher link utilization Native P2P can result in some peers experiencing very long download completion time Native P2P can result in much larger variance in link utilization

P4PWG July Meeting 13 Evaluation – BitTorrent on AT&T Compared to P4P, native P2P can result in  1.6x download completion time  3x higher link utilization Some peers can experience very long download completion time with native P2P Link utilization variance can be larger for native P2P

P4PWG July Meeting 14 Evaluation – Liveswarms on PlanetLab Liveswarms* is a P2P-based video streaming application, which adapts BitTorrent protocol to video streaming context Run liveswarms on 53 PlanetLab nodes for 900 seconds P4P and native liveswarms achieve roughly the same amount of throughput P4P reduces link load  Average link load saving is 34MB  Maximum average link load saving is 60% Native liveswarms:1Mbps P4P liveswarms: 432Kbps *Michael Piatek, Colin Dixon, Arvind Krishnamurthy, Tom Anderson. LiveSwarms: Adapting BitTorrent for end host multicast. Technical report: UW-CSE

P4PWG July Meeting 15 Contact and Acknowledgement For further details, please refer to our technical report Yale/DCS TR-1377 It is still a work-in-progress and changes rapidly Questions/comments are highly welcome:  Haiyong Xie  Y. Richard Yang Acknowledgements We would like to thank Charles Kalmanek (AT&T Labs), Marty Lafferty (DCIA), Doug Pasko (Verizon), Laird Popkin (Pando), Keith Ross (Polytechnic), Ke Xu (Tsinghua Univ.) for suggestions, discussions and feedback.