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Distributed Computation of Centrality Measures in Dynamic Complex Networks

Sharifzadeh Kermani, Zahra | 2018

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  1. Type of Document: M.Sc. Thesis
  2. Language: English
  3. Document No: 54744 (52)
  4. University: Sharif University of Technology, International Campus, Kish Island
  5. Department: Science and Engineering
  6. Advisor(s): Hematyar, Ali Mohammad Afshin; Kavousi, Kaveh
  7. Abstract:
  8. Complex networks represent a wide diversity of systems in nature and human interactions. Networks are graphs that describe the structures of interacting systems and give significant information about the patterns of connections between the nodes in a particular system. In turn, having knowledge about the structure of networks and their arrangements enables one to make certain types of predictions about their behavior of network.Network methods have had profound influence in many domains and fields in the past decade. Centrality measures are very important tool for analysis complex networks, in real-world complex networks are heterogeneous structures, all their components such as nodes (vertices), edges and subgraphs are not carry the same role or importance in the functions performed by the networks: some elements are more critical and important than others. Understanding the roles of the components of a network is crucial for understanding the behavior of the network as a whole. The aim of this research is to give a distributed algorithm for centrality computation. In this thesis, we distribute algorithm to calculate centrality based on shortest path layers, which this algorithm use SPL method to discover shortest paths between nodes and use them to compute centrality measures, also this algorithm can compute degree, betweenness and closeness centrality [1]
  9. Keywords:
  10. Complex Network ; Betweenness Centrality ; Centrality Metrics ; Nodes Centrality ; Closeness Centrality ; Shortest Path Layer (SPL)

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