BrocadeLandmark Routing on P2P Networks

Gisik Kwon

April 9, 2002

MotivationProblems 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)

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.

Network in reality

Transit-stub topology, disparate resources per node Result: Inefficient inter-domain routing

AS-2

P2P Overlay Network

AS-1

AS-3

S R

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

AS-2

P2P Network

AS-1

AS-3

Brocade Layer

S R

Original Route

Brocade Route

Brocade Architecture

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

• 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.

Case Study - Brocade On TapestryTapestry: 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

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

Entering the BrocadeRoute: 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

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 Decision 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

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

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

Appendix

Tapestry

Bloom filter

Brief TapestrySuffix matching ( similar to Plaxton ) Incrementally routing digital by digital

Maximum hops : logb(N)

6789

B4F8

9098

7598

4598

Msg to 4598

B437

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

0642

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 <O:1234,S:B4F8>

Surrogate Routing

Publishing : basic procedure

Similar to locating1. Server send msg and pretends to locate the object2. Find the surrogate node as the “root” for the Obj.3. Save the related info there, such as <O,S>

Server :B4F8

1234

8724

F734

B234

6234 <O:1234,S:B4F8>

Surrogate Routing

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

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

Bloom filter(2)

Procedure BloomFilter(set A, hash_functions, integer m) returns filter filter = allocate m bits initialized to 0

foreach ai in A:

foreach hash function hj:

filter[hj(ai)] = 1 end foreach end foreach return filter

 Procedure MembershipTest (elm, filter, hash_functions) returns yes/no

foreach hash function hj:

if filter[hj(elm)] != 1 return No end foreach return Yes