Transcript Slide 1
PeerWise Discovery and Negotiation of Faster Paths
Cristian Lumezanu Dave Levin Neil Spring
Routing Overlays
Potential BENEFIT is HIGH Deployment COST is LOW PeerWise Discovery and Negotiation of Faster Paths HotNets 2007
Scalability?
A C B Probing should be done more selectively PeerWise Discovery and Negotiation of Faster Paths HotNets 2007
Fairness?
cost
benefit > 1 cost
benefit
< 1 Routing overlays should include an incentive mechanism PeerWise Discovery and Negotiation of Faster Paths HotNets 2007
PeerWise
PeerWise Nodes negotiate and establish pairwise connections to each other Nodes that can help each other find better paths peer Motivation Models autonomous system peerings in the Internet Overlays built on self-interest rather than altruism Cost-benefit ratio known before committing any resources PeerWise Discovery and Negotiation of Faster Paths HotNets 2007
PeerWise
D 30ms 50ms A B 40ms 60ms C
PeerWise Discovery and Negotiation of Faster Paths HotNets 2007
PeerWise properties
PeerWise Discovery and Negotiation of Faster Paths HotNets 2007
PeerWise properties
PeerWise Discovery and Negotiation of Faster Paths HotNets 2007
Is mutual advantage common?
G E B D F
PEERING SCORE
A Difference between the number of routes each node uses the other for after all peerings have been established
EXPERIMENT SETUP
• • • PeerWise prototype with global knowledge 256 DNS server data set gathered using the King method Each node sends data to all other nodes
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Is mutual advantage common?
100 74
74% of the pairs of nodes are happy with existing peerings
0 20 peering score
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PeerWise properties
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Finding shorter detours
B 10ms 10ms
At least 66% of the pairs of nodes in our datasets are long sides in TIVs
A C 100ms
Triangle inequality violations indicate the existence of shorter one-hop detours
flaws in
We use network coordinates to find triangle inequality violations PeerWise Discovery and Negotiation of Faster Paths HotNets 2007
20ms
Network coordinates and TIVs
B 39ms Internet Metric space 38ms B 42ms A 62ms
TIVs allowed AC > AB + BC
C C A 26ms
error(AC) = -36ms No TIVs AC < AB + BC Long sides shrink Sum of short sides grows PeerWise Discovery and Negotiation of Faster Paths HotNets 2007
Embedding errors and TIVs
If long sides shrink The more negative the embedding error of an edge, the higher the probability that the edge is a long side in a TIV …and thus has a one-hop shorter detour If sum of short sides grows The more positive the embedding error of an edge, the higher the probability that the edge is a short side in a TIV …and thus is part of a one-hop shorter detour PeerWise Discovery and Negotiation of Faster Paths HotNets 2007
PeerWise properties
PeerWise Discovery and Negotiation of Faster Paths HotNets 2007
Performance
best one-hop path
100
direct path PeerWise reduces latency by an average of 20%
0 100 Latency (ms)
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Conclusions
PeerWise Discovery and Negotiation of Faster Paths HotNets 2007
Future Work
Future Work Why is there mutual advantage?
Extensions for low-loss and failure-free paths Deployment PeerWise Discovery and Negotiation of Faster Paths HotNets 2007
Are one-hop detours enough?
100 75
best one-hop detour path direct path 3% of detour paths are longer than 100ms 25% of direct paths are longer than 100ms 50% improvement in average latency
0 100 Latency (ms)
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Connectivity
100
60% of nodes can reach more than 60% of their destinations, with limited knowledge limited knowledge (32 neighbors) global knowledge
40 22 0 detour score 60 Percentage of destinations that a node can reach using its peerings, out of all reachable destinations
78% of nodes can reach more than 60% of their destinations, with global knowledge
100
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Embedding errors and TIVs
The more negative the embedding error of an edge, the higher the probability that the edge is a long side in a TIV …and thus has a one-hop shorter detour The more positive the embedding error of an edge, the higher the probability that the edge is a short side in a TIV …and thus is part of a one-hop shorter detour TIV SCORE
Percentage of how many times a pair of nodes forms a long side in a TIV out of total number of presences in TIVs
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more long sides
Embedding errors and TIVs
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As the estimation error becomes more negative the nodes form more and more long sides
50
more short sides
0 -200 0 embedding error estimated distance – real distance
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