Post on 03-Jan-2016
description
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