iPlane : An Information Plane for Distributed Services

1. iPlane: An Information Plane for Distributed Services Harsha V. Madhyastha, Tomas Isdal, Michael Piatek Colin Dixon,Thomas Anderson, Arvind Krishnamurthy University of Washington Arun Venkataramani University of Massachusetts Amherst

2. Distributed Services need Information • Content Distribution Networks (Akamai) • Direct clients to nearby servers • Peer-to-peer file distribution (BitTorrent) • Select peers that provide good performance • VoIP applications (Skype) • Choose detour nodes to bridge hosts behind NATs

3. Problem: Internet is Opaque P4 (Chicago) P1 (Seattle) BitTorrent: How to determine which peers are good? Download from all peers P5 S Internet (Paris) (Portland) P3 (Atlanta) P2(Rio)

4. Solution: Information Plane P4 (Chicago) P1 (Seattle) (Portland) P5 S Internet (Paris) Information Plane Which peers are good for me? P3 (Atlanta) P1 ,P3 P2(Rio)

5. iPlane • A service that predicts path performance on the Internet • Maps the Internet’s topology from vantage points • Uses a structural model of Internet performance • Applications query system to predict unmeasured paths • Evaluation shows iPlane’s predictions help • BitTorrent • CDN • VoIP

6. Mapping and Modeling the Internet • Measure the properties of Internet’s topology • Repeated daily from several vantage points • Need a model to predict performance between arbitrary end-hosts • Can only measure paths from vantage points • Our approach: Predict route through the Internet • Estimate end-to-end path properties as combination of link properties

7. Internet Model for Path Prediction V3 (Chicago) V1 (Seattle) Route similarity: Route from nearby vantage point intersects closer to the source Identify candidate paths by intersecting observed routes I D S (Portland) (Paris) Actual path not known Choose candidate path that models Internet routing V2(Sao Paolo)

8. Measuring the Core V2 V1 • Performance prediction needs properties of all links • Measure links in the core • Gather topology at central server • Select paths that cover all links • Measure selected paths for • loss-rate • bandwidth capacity • available bandwidth • Derive link properties from path measurements R1 R2 D

9. Measuring the Edge • Challenges in measuring access links • Many end-hosts are behind NATs • Firewalls raise alarms on probe packets • Our solution • Participate in BitTorrent swarms • Popular application – wide coverage of end-hosts • Passively monitor TCP connections to measure access link properties • Will not raise alarms as these packets are expected

10. Case Study: Improving BitTorrent • Default BitTorrent • Tracker maintains list of all nodes in the swarm • Any client contacts the tracker to discover peers • Tracker returns random subset of nodes as peers • Our modification to BitTorrent • Tracker returns peers with good predicted performance with the client

11. Improving BitTorrent • 150 nodes participated in a swarm for a 50 MB file • 80% of peers have significantly lesser download times

12. Conclusions • We presented iPlane: an information plane • Maintains a map of the Internet’s routing topology • Predicts path properties between arbitrary end-hosts • Queriable by applications for path performance on the Internet • Our evaluation of iPlane shows • Estimates of path properties are accurate • Can help applications deliver better performance

13. For more information • iPlane: An Information Plane for Distributed Services - OSDI 2006 http://iplane.cs.washington.edu