Abstract

A distributed consensus algorithm for estimating the degree distribution of a graph is proposed. The proposed algorithm is based on average consensus and in-network empirical mass function estimation. It is fully distributed in the sense that each node in the network only needs to know its own degree, and nodes do not need to be labeled. The algorithm works for any connected graph structure in the presence of communication noise. The performance of the algorithm is analyzed. A discussion on how the properties of the graph degree distribution can be exploited for post-processing after consensus is reached is given. Simulation results corroborating the theory are also provided.

Original languageEnglish (US)
Title of host publication2016 IEEE Global Communications Conference, GLOBECOM 2016 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781509013289
DOIs
StatePublished - Feb 2 2017
Event59th IEEE Global Communications Conference, GLOBECOM 2016 - Washington, United States
Duration: Dec 4 2016Dec 8 2016

Other

Other59th IEEE Global Communications Conference, GLOBECOM 2016
CountryUnited States
CityWashington
Period12/4/1612/8/16

Keywords

  • Average Consensus
  • Degree Distribution
  • Degree Matrix
  • Probability Mass Function
  • Wireless Sensor Networks

ASJC Scopus subject areas

  • Computational Theory and Mathematics
  • Computer Networks and Communications
  • Hardware and Architecture
  • Safety, Risk, Reliability and Quality

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  • Cite this

    Zhang, S., Lee, J., Tepedelenlioglu, C., & Spanias, A. (2017). Distributed estimation of the degree distribution in wireless sensor networks. In 2016 IEEE Global Communications Conference, GLOBECOM 2016 - Proceedings [7841740] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/GLOCOM.2016.7841740