1. Brocade Landmark Routing on P2P Networks Gisik Kwon April 9, 2002

2. Motivation Problems with existing P2P systems Existing systems : CAN, Chord, Tapestry, Pastry Constrained by the theoretical approach adopted, nodes are treated uniformly Routing algorithms are decoupled from underlying topology and node capability Result: Sub-optimal performance  Due to 1) the asymmetry of nodes in reality  Less powerful nodes can be overloaded  Due to 2) the lack of structure  No advantage of the aggregated knowleges of the network P2P does not need to operate in the pure P2P style A secondary overlay network on top of existing system(e.g., Tapestry)

3. Brocade A philosophy: A system is more efficient when it is organized Respect the differences and take advantage of those that are more powerful – Supernodes! Fast/well-connected/situated near network access points Supernodes have better knowledge of underlying network characteristics. Benefit from aggregation.

4. Network in reality Transit-stub topology, disparate resources per node Result: Inefficient inter-domain routing AS-2 P2P Overlay Network AS-1 AS-3 SR

5. Landmark Routing Goals Eliminate unnecessary wide-area hops for inter-domain messages Eliminate traffic going through high latency, congested stub links Reduce wide-area bandwidth utilization

6. AS-2 P2P Network AS-1 AS-3 Brocade Layer SR Original Route Brocade Route Brocade Architecture

7. Intuitive mechanisms Intuition: route quickly to destination domain Organize group of supernodes into secondary overlay Sender (S) sends message to local supernode SN1 SN1 finds and routes message to supernode SN2 near receiver R SN1 uses Tapestry object location to find SN2 SN2 sends message to R via normal routing

8. Overlay nodes are grouped by their supernodes Supernodes treat their overlay nodes as objects that they possess Routing on Brocade => Object Location. Use your favorite mechanism: Tapestry, CAN, Chord, Pastry Message filtering: only send inter-domain messages to Brocade.

9. Case Study - Brocade On Tapestry Tapestry: A novel wide-area fault-tolerant location and routing infrastructure Construction Supernode selection Significant processing power Minimum number of ip hops to wide-area network High bandwidth outgoing link  So, gateway routers or machines close by those Existing connections among supernodes as Brocade links

10. Classifying Traffic Brocade not useful for intra-domain messages P2P layer should exploit some locality (Tapestry) Undesirable processing overhead Classifying traffic by destination Proximity caches: - Every overlay node keeps list of nodes it knows to be local - Need not be optimal Cover set: - Supernode keeps list of all nodes in its domain - Acts as authority on local vs. distant traffic AS-1 S

11. Entering the Brocade Route: Sender  Supernode Naïve Brocade: Tapestry routing unchanged. Message gets onto the Brocade overlay if a supernode is encountered on its route. Advantage: simple, no modification to ordinary nodes. Disadvantage: possibility of hitting a supernode in Tapestry routing small. IP Snooping Brocade: Supernodes snoop IP packets to intercept Tapestry messages. Advantage: - No modification to ordinary nodes. - High possibility of encountering supernodes because supernodes are situated near the edge of local networks. Disadvantage: difficult to implement

12. Entering the Brocade Directed Brocade: Each overlay node keep info about its supernode and decides by its own whether to send a message to supernode directly. Feasible: only local information required D ecision Engine: Destination is in my cover set? Send to supernode Ordinary Tapestry Routing No Yes A small cache storing most frequently used nodes in its cover set will do the trick. Query locality will make hit rate high Consequences of mistakes aren’t expensive

13. Inter-supernode Routing Route: Supernode (sender)  Supernode (receiver) Locate receiver’s supernode given destination nodeID Use Tapestry object location or Bloom filter Tapestry Routing mesh w/ built in proximity metrics Location exploits locality (finds closer objects faster) Finding supernodes Supernode “publishes” cover set on brocade layer as locally stored objects To route to node N, locate server on brocade storing N

14. Brocade Summary P2P systems assume uniformity  Extraneous hops through backbone to domains  Routing across congested stubs links Constrain inter-domain routing Remove unnecessary routing through stubs Reduce expected inter-domain hops Result: lower latency, less bandwidth utilization

15. Appendix Tapestry Bloom filter

16. Brief Tapestry Suffix matching ( similar to Plaxton ) Incrementally routing digital by digital Maximum hops : log b (N) 6789 B4F8 9098 7598 4598 Msg to 4598 B437

17. Routing : Neighbor maps A table with b*log b (N) entries The i-th level neighbor share (i-1) suffix chunks Entry( i, j ) Pointer to the neighbor “ j” + (i-1) suffix 0642

18. Locating : basic procedure 4 phrases locating Map the Object ID to a “virtual” Node ID Route the request to that node Arrive the surrogate or“root for the object Direct to the server Client : B4F8 Server : B4F8 1234 8724 F734 B234 6234 Surrogate Routing

19. Publishing : basic procedure Similar to locating 1. Server send msg and pretends to locate the object 2. Find the surrogate node as the “root” for the Obj. 3. Save the related info there, such as Server :B4F8 1234 8724 F734 B234 6234 Surrogate Routing

20. Insert a new node: basic procedure 1. Get an Node ID 2. Begin with a “Gateway node” G 3. Pretends to route to itself 4. Establish nearly optimal neighbor map during the “pseudo routing” by coping & Choosing nearest ones. 5. Go back and notify neighbors Gateway node : B4F8 8724 F734 B234 6234 Surrogate Routing New node : 1234

21. Bloom filter(1) Set S Query: is x in S? If filter says no, x is not in S. If filter says yes, x is probably in S. Set is bitmap: 010110 Sequence of hash functions f(x, i) –Independent on x, i –F(x,i) = 0 or 1 If f(x,i) is 1 for i values: –0,2,3 not present –2,4 probably present

22. Bloom filter(2) Procedure BloomFilter(set A, hash_functions, integer m) returns filter filter = allocate m bits initialized to 0 foreach a i in A : foreach hash function h j : filter[ h j (a i ) ] = 1 end foreach return filter Procedure MembershipTest (elm, filter, hash_functions) returns yes/no foreach hash function h j : if filter[ h j (elm) ] != 1 return No end foreach return Yes