Achieving scale: Large scale active measurements from PlanetLab

Transcription

1 Achieving scale: Large scale active measurements from PlanetLab Marc-Olivier Buob, Jordan Augé (UPMC) 4th PhD School on Traffic Monitoring and Analysis (TMA) April 15th, 2014 London, UK OneLab FUTURE INTERNET TEST BEDS Achieving scale: Large scale active measurements from PlanetLab 1/ 1 UPMC

2 Part I : a brief overview of Internet routing Achieving scale: Large scale active measurements from PlanetLab 2/ 1 UPMC

3 Overview of Internet routing Autonomous Systems The Internet is made of more than interconnected domains called Autonomous Systems (ASes). Each AS corresponds to a set of IP equipments control by a single entity (ISP, University, firm,...). Achieving scale: Large scale active measurements from PlanetLab 3/ 1 UPMC

4 Overview of Internet routing IP fowarding Each IP packet carries in its header the IP destination. Each IP equipment forwards incoming packets according to its forwarding table to a nexthop. Achieving scale: Large scale active measurements from PlanetLab 4/ 1 UPMC

5 Overview of Internet routing Interior Gateway Protocol (IGP) Inside an AS, destinations are routed thanks to an IGP (OSPF, RIP,...). IGP computes shortest paths towards all the interior destinations. Achieving scale: Large scale active measurements from PlanetLab 5/ 1 UPMC

6 Overview of Internet routing Border Gateway Protocol (BGP) (1/3) BGP is used to map exterior destination with an egress point called BGP next hop. For each destination, BGP router elects its best BGP route among those it learns. Then, it routes the traffic this egress point using its IGP routing. Achieving scale: Large scale active measurements from PlanetLab 6/ 1 UPMC

7 Overview of Internet routing Border Gateway Protocol (BGP) (2/3) ASes uses BGP to reflect their business agreements : transit : the client AS pays its provider AS whenever they exchanges traffic. peering : the traffic freely exchanged between the both ASes and their clients. ASes should prefer BGP routes maximizing their benefits. ASes should not reannounce BGP routes which could make it loose money On Inferring Autonomous System Relationships in the Internet, L. Gao, TON Achieving scale: Large scale active measurements from PlanetLab 7/ 1 UPMC

8 Overview of Internet routing Border Gateway Protocol (BGP) (3/3) Economically valid inter AS-paths are thus hierarchical. Business relationships directly impact overall routing; however, they are most of time not public! Achieving scale: Large scale active measurements from PlanetLab 8/ 1 UPMC

9 Challenges Internet is a complex network. Its architecture and behavior is not well known (routing, interconnection, geolocation, infrastructure,...). Measurement reveals information about this network. How to use measurements to reverse engineer the Internet? What is the bias and the artefacts induced by those measurements? How to improve the measurements? Achieving scale: Large scale active measurements from PlanetLab 9/ 1 UPMC

10 Part II : Challenges in distributed measurements Achieving scale: Large scale active measurements from PlanetLab 10/ 1 UPMC

11 Measuring the underlay topology Achieving scale: Large scale active measurements from PlanetLab 11/ 1 UPMC

12 Measuring the underlay topology Achieving scale: Large scale active measurements from PlanetLab 11/ 1 UPMC

13 Measuring the underlay topology Achieving scale: Large scale active measurements from PlanetLab 11/ 1 UPMC

14 Measuring the underlay topology Achieving scale: Large scale active measurements from PlanetLab 11/ 1 UPMC

15 Measuring the underlay topology Achieving scale: Large scale active measurements from PlanetLab 11/ 1 UPMC

16 Measuring the underlay topology Achieving scale: Large scale active measurements from PlanetLab 11/ 1 UPMC

17 Measuring the underlay topology Achieving scale: Large scale active measurements from PlanetLab 11/ 1 UPMC

18 Measuring the underlay topology Achieving scale: Large scale active measurements from PlanetLab 11/ 1 UPMC

19 Measuring the underlay topology Achieving scale: Large scale active measurements from PlanetLab 11/ 1 UPMC

20 Measuring the underlay topology Achieving scale: Large scale active measurements from PlanetLab 11/ 1 UPMC

21 A black box approach Either search for evidences... eg. a traceroute proves I have a path from A to B or apply inferences techniques Usual tools : ping, traceroute, etc. Achieving scale: Large scale active measurements from PlanetLab 12/ 1 UPMC

22 Avoiding measurement artefacts : Paris Traceroute (1/2) Regular traceroute causes artefacts in measurements in presence of LB Achieving scale: Large scale active measurements from PlanetLab 13/ 1 UPMC

23 Avoiding measurement artefacts : Paris Traceroute (1/2) Regular traceroute causes artefacts in measurements in presence of LB Achieving scale: Large scale active measurements from PlanetLab 13/ 1 UPMC

24 Avoiding measurement artefacts : Paris Traceroute (1/2) Regular traceroute causes artefacts in measurements in presence of LB Achieving scale: Large scale active measurements from PlanetLab 13/ 1 UPMC

25 Avoiding measurement artefacts : Paris Traceroute (2/2) Measuring per-flow and per-destination load balancers em Paris Traceroute maintains a constant flow id to accurately measure Per-Flow LB em Extension to measure Per-Destination LB Exhaustive measurements of load-balanced paths MDA (Multipath Discovery Algorithm) em allows discovery of all paths between source and destination/prefix with a given level of confidence Achieving scale: Large scale active measurements from PlanetLab 14/ 1 UPMC

26 The need for a large number of vantage points Achieving scale: Large scale active measurements from PlanetLab 15/ 1 UPMC

27 The need for a large number of vantage points Achieving scale: Large scale active measurements from PlanetLab 15/ 1 UPMC

28 Measuring the dynamism Need to reduce the network load also allows to perform measurement rounds faster Techniques : reducing redundancy Efficient probing Efficient distributed algorithms (need cooperation) Exploit low variability of many Internet regions in small timescales Achieving scale: Large scale active measurements from PlanetLab 16/ 1 UPMC

29 Available infrastructures for measurements Specialized measurement platforms Archipelago, DIMES, Aqualab, iplane, RIPE Atlas, etc. Most are not open for on-demand measurements, granularity is coarse (hours to days) General-purpose testbeds PlanetLab, etc. Achieving scale: Large scale active measurements from PlanetLab 17/ 1 UPMC

30 TDMI : TopHat dedicated measurement infrastructure A measurement platform distributed on PlanetLab 400 active nodes On-demand measurements + full-mesh traceroute every 5 min Serves users of the testbeds + our research on distributed measurements Achieving scale: Large scale active measurements from PlanetLab 18/ 1 UPMC

31 TopHat Dedicated Measurement Architecture Achieving scale: Large scale active measurements from PlanetLab 19/ 1 UPMC

32 A use case for distributed measurements Achieving scale: Large scale active measurements from PlanetLab 20/ 1 UPMC

33 A use case for distributed measurements Achieving scale: Large scale active measurements from PlanetLab 20/ 1 UPMC

34 A use case for distributed measurements Achieving scale: Large scale active measurements from PlanetLab 20/ 1 UPMC

35 TopHat & TDMI architecture Achieving scale: Large scale active measurements from PlanetLab 21/ 1 UPMC

36 The toughest challenge The lack of Ground truth Achieving scale: Large scale active measurements from PlanetLab 22/ 1 UPMC

37 Part III : TopHat, Manifold Achieving scale: Large scale active measurements from PlanetLab 23/ 1 UPMC

38 Handling large heterogeneous and distributed datasets An ecosystem of measurement data sources 1 Several datasets are publicly available : Some provides the same type of information (TDMI, ark) Some can enrich this information (Maxmind, TeamCymru) 2 By combining those data sources we could answer to new questions : Countries traversed by a given traceroute measurement? Number of ASes traversed by this traceroute measurements? Achieving scale: Large scale active measurements from PlanetLab 24/ 1 UPMC

39 Handling large heterogeneous and distributed datasets The need of an intelligent mediator 1 Heterogeneous data (API, DB, CSV,...) = combination? 2 Data are spread across the network = aggregation? 3 TopHat provides a single entry point allowing to transparently query those data sources. Achieving scale: Large scale active measurements from PlanetLab 25/ 1 UPMC

40 Handling large heterogeneous and distributed datasets Express query across the network using Manifold 1 A common language adopted by the actors (users, Manifold/TopHat, platforms) Announces : to announces resources ( BGP). Queries : to request data. Records : to transports data. 2 Manifold deduces for each incoming queries who are the relevant actors, what to query, and how to combine the records. 3 Heterogeneity is managed using translators. Achieving scale: Large scale active measurements from PlanetLab 26/ 1 UPMC

41 How does it work? Announces Achieving scale: Large scale active measurements from PlanetLab 27/ 1 UPMC

42 How does it work? Query Achieving scale: Large scale active measurements from PlanetLab 28/ 1 UPMC

43 How does it work? Query dispatching Achieving scale: Large scale active measurements from PlanetLab 29/ 1 UPMC

44 How does it work? Record aggregation Achieving scale: Large scale active measurements from PlanetLab 30/ 1 UPMC

45 Part IV : A few words about DNS Achieving scale: Large scale active measurements from PlanetLab 31/ 1 UPMC

46 The DNS architecture Achieving scale: Large scale active measurements from PlanetLab 32/ 1 UPMC

47 The DNS architecture Achieving scale: Large scale active measurements from PlanetLab 32/ 1 UPMC

48 The DNS architecture Achieving scale: Large scale active measurements from PlanetLab 32/ 1 UPMC

49 The DNS architecture Achieving scale: Large scale active measurements from PlanetLab 32/ 1 UPMC

50 About PlanetLab Achieving scale: Large scale active measurements from PlanetLab 33/ 1 UPMC