Workshop on Online Social Networks

1
Social Network Analysis for Routing in
DisconnectedDelay-Tolerant MANETs

• Workshop on Online Social Networks
• Microsoft Research Cambridge
• Elizabeth Daly and Mads Haahr
• Distributed Systems Group,
• Computer Science Department
• Trinity College, Dublin

2
Introduction and Motivation

• Routing in a disconnected network graph
• Traditional MANET Routing protocols fail
• Store-carry-forward model used
• Global view of network unavailable and volatile
• Social Networks
• Milgrams Small world
• Hsu and Helmys analysis of wireless network

3
Related Work

• Deterministic
• Assumes node movements are deterministic
• DataMULEs or Message Ferries
• Assumes given nodes travel around the network
• Epidemic
• Expensive in terms of resources
• History or Prediction
• Captures direct and indirect social relationships
• Problem
• What if destination node is unknown to
  neighbouring nodes

4
Solution

• Exploit Social Network Analysis Techniques in
  order to
• Identify bridging ties
• Centrality
• Identify clusters
• Similarity

5
Centrality Metrics Freeman 1977,1979

• Degree centrality
• popular nodes in the network
• Closeness centrality
• the distance of a given node to each node in the
  network
• Betweenness centrality
• the extent to which a node can facilitate
  communication to other nodes in the network

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Ego Network Centrality Measures

• Analysis of a nodes local neighbourhood

Degree Centrality
Betweenness Centrality
Closeness Centrality
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Egocentric Betweenness Correlation
Marsden 2002
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Similarity

• Social networks exhibit clustering
• Increased common neighbours increases probability
  of a relationship Newman 2001
• Similarity metric may be used to predict future
  interactions Liben-Nowell,Kleinberg 2003
• Represents similarity of social circles

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SimBet Routing
Add node encounters Update betweenness Update
similarity
Add node encounters Update betweenness Update
similarity
Deliver msgs
HELLO
Exchange encounters
Compare SimBet Utility
Exchange Summary Vector
Exchange messages
10
Betweenness Utility Calculation

• Node contacts represented in symmetric adjacency
  matrix
• if there is a contact between i and j
• otherwise
• Ego betweenness is given as the sum of the
  reciprocals of

Everett and Borgatti 2005
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Similarity Utility Calculation

• Indirect Node contacts learnt during a node
  encounter is represented in and additional matrix
  
• Node similarity is a simple count of common
  neighbours

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SimBet Utility Calculation

• Goal to select node that represents the best
  trade off across both attributes

• Combined

where
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Simulation Setup

• Trace based simulation using MIT Reality Mining
  project data set
• 100 users carrying Nokia 6660 for 9 months
• Bluetooth sightings used as opportunity for data
  exchange
• Comparison
• Epidemic Routing Vahdat and Becker 2000
• PRoPHET Lindgren, Doria and Schelén 2004
• Scenario 1 Each node generates a single message
  for all other nodes
• Scenario 2 Message exchange between least
  connected nodes

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MIT Data set Egocentric Betweenness
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Egocentric Betweenness Correlation
Pearsons Correlation
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Egocentric Betweenness
Friendship network Eagle and Pentland
Egocentric Betweenness
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Delivery Performance
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Average End-To-End Delay
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Average Number of Hops
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Total Number of Forwards
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Delivery Performance between least connected nodes
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Conclusion

• Simple metrics for capturing network social
  structure suitable for disconnected
  delay-tolerant MANETs
• Egocentric Betweenness
• CentralitySimilarity
• Achieves comparable delivery performance compared
  to Epidemic Routing
• But with lower delivery overhead
• Achieves delivery performance between least
  connected nodes

23

• Questions