mapping the internet topology via multiple agents
DESCRIPTION
Mapping the Internet Topology Via Multiple Agents. What does the internet look like?. Why do we care?. While communication protocols will work correctly on ANY topology ….they may not be efficient for some topologies Knowledge of the topology can aid in optimizing protocols. Topics. - PowerPoint PPT PresentationTRANSCRIPT
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Mapping the Internet Topology Via Multiple Agents
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What does the internet look like?
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Why do we care?
• While communication protocols will work correctly on ANY topology
….they may not be efficient for some topologies
• Knowledge of the topology can aid in optimizing protocols
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Topics
• Power laws in the internet topology
• Sampling bias in existing topology measurements
• The DIMES project
• Potential applications
• Open issues
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Mapping the Internet
• Required characteristics:– connectivity– delays
• Metrics– In/Outdegree– Distance (delay – problematic definition)
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Problem definition
G – (un)directed graphN – number of nodesE – number of edgesdv – outdegree of a node v
fd – frequency of an outdegreeP(h) – number of pairs in the “h-hop
neighborhood”
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On Power-law Relationships of the Internet Topology
Oct. 1999, Faloutsos Bros.
Mapped the internet at the AS and router level using BGP route views
Data sets: – Nov. ’97: 3015 nodes, 5156 edges– Apr. ’98: 3530 nodes, 6432 edges– Dec. ’98: 4389 nodes, 8256 edges
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Outdegree Exponent Power Law
fd ~ d^σ
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Other places that people look for power laws…
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SCIENCE CITATION INDEX
( = 3)
Nodes: papers Links: citations
(S. Redner, 1998)
P(k) ~k-
2212
25
1736 PRL papers (1988)
Witten-SanderPRL 1981
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Sex-web
Nodes: people (Females; Males)Links: sexual relationships
Liljeros et al. Nature 2001
4781 Swedes; 18-74; 59% response rate.
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Recall – the Faloutsos graph
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Is It Really Power Law?
• Sampling bias could exist
• Crovella article title
• Target – find out if bias exists in prevailing measurement methods, and identify the sources for this bias.
• Configuration – graph model, sampling method, distributions, why this is similar to currently used methods
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Results
• Erdos – Renyi + graphs
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Sources of sampling bias
• Disproportional sampling of nodes
• Disproportional sampling of edges
• Conclusion
• Identify problems in existing measurement methods (Faloutsos, Caida)
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Analysis of Bias Cause
• Explanation– Better coverage with more measurement
sources
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DIMES
• Targets
• How we try to solve the problem
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DIMES Platform
• Description
• Screenshot
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Internet according to DIMES
• maps
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Application
• Research– Simulations
• Developing new algs, protocols• Evolution (how will the internet look like in 2020?)• Testing new tools, manufacturing scenarios
– “pure” research• Studying the internet “behavior”, growth• Developing models to describe it
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More Application
• Potentially commercial– Improve existing algs’ using knowledge about
the characteristics of the internet.• Multicast alg’• Low – priority packet routing
– Identify (and work around?) network vulnerabilities
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Open Issues
• Measuring delays– Asymmetry– round trip is problematic– triangle inequality doesn’t necessarily hold
• Mapping interfaces to server
• Identifying POPs
• Identifying motiffs