United States - Complex Networks - Lecture Slides, Slides of Data Communication Systems and Computer Networks

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The United States air transportation

network analysis

Introduction

• The problem and its importance
• Challenges
• Missing pieces
• Previous Studies
• Related works
• Key components of my research

The problem and its importance

• Problem

• Analysis the air transportation network in the U.S.
  • Network driven by profits and politics
  • Better understand the network structure not maximize utility

• Importance

• Economy: transport of good and services
• Air traffic flow: convenience
• Health studies: propagation of diseases

Outline

• The problem and its importance
• Challenges
• Missing pieces
• Previous Studies
• Related works
• Key components of my research

Outline

• The problem and its importance
• Challenges
• Missing pieces
• Previous Studies
• Related works
• Key components of my research

Missing pieces

• Sufficient amount of researches on the

network with focuses on utility optimization.

• Commercial enterprises: OAG and Innovata

• But … lack of research on analyzing the

network features studied in class.

Previous studies

• No analysis on the network features related to

this class.

• Related studies for reference and metrics to

analyze.

Outline

• The problem and its importance
• Challenges
• Missing pieces
• Previous Studies
• Related works
• Key components of my research

WAN

• Network

• Nodes: cities
• Edges: flight routes

• Data

• OAG
• November 1, 2000 to November 7, 2000
• Four years gap
• Scheduled flights from all airlines

WAN

• Small world property

• Comparison to a random WAN
  • Shortest path length 4.4. Worst case is 15.
  • High clustering coefficient 0.62 (WAN) vs. 0.049.

• Power law cumulative degree distribution

• Tail of degree distribution monotonically

decreases (preferential attachment)

• Alpha 1.0. Size of network increases so does the

degree of the nodes.

WAN

• Most connected versus must central (betweenness centrality) cities [1].
  • Circle represents WAN
  • Dotted line represents a randomized WAN
  • Smaller degree nodes higher betweenness
  • Small degree nodes are more central: Anchorage in Alaska

WAN

Identify most connected and most central cities.

• (b) Top 25 most connected cities [1].
• (c) Top 25 most central cities (betweenness)[1].

WAN

• Identify hubs in WAN [1]. (a) z >= 2.5 are hubs and z < 2.5 non hubs (RB) Majority of hubs are well connected within their communities. (c) Non hub (G), hub(Y) and connector hubs (Gy) Cities that are not hubs rarely have links to other communities.

ANI

• Network

• Nodes: airports
• Un-weighted edges: existence of flight routes
• Weighted edges: amount of flight routes per week
• 79 nodes with 6162 distinct paths

• Data

• Timetable for air services in India.
• Week of January 12, 2004.