Adaptive Approximation Algorithm for Community Structure Detection

Community structure is defined as a subgraph such that there is a higher density of edges within the subgraph than between them. This has applications in many domains, not only in computer networks, but also in computational biology, social research, life sciences and physics. We focuses on complex, dynamic, and evolving over time, yet often greatly affected by uncertain factors, which may arise in many forms, including natural or man-made interferences.

Objectives:

  • Develop mathematical models and efficient approximation algorithms to determine the community structure of a given network
  • Handle the dynamic and evolution of community structures; provide a mathematical framework for several existing problems in dynamic networks such as routing protocols in DTN and MANETs, network design and management