Exploring unknown paths in networks based on multiple random walks

  • Authors:

  • Cunlai Pu;Jian Yang;Ruihua Miao;Wenjiang Pei

  • Affiliations:

  • School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing, People's Republic of China;School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing, People's Republic of China;School of Information Science and Engineering, Southeast University, Nanjing, People's Republic of China;School of Information Science and Engineering, Southeast University, Nanjing, People's Republic of China

  • Venue:
  • IScIDE'12 Proceedings of the third Sino-foreign-interchange conference on Intelligent Science and Intelligent Data Engineering
  • Year:
  • 2012

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Abstract

We study the problem of exploring unknown paths in networks through multiple random walks. It is assumed that a path is explored if it has been passed through by a random walker from the initial node to the terminal node continuously. We derive probability θ′(t) that a given path in a network is explored by one or more random walkers in t steps on condition that there are many random walkers traveling on the network. Results show that more random walkers are better for exploring the path. The larger length l of the path is, the smaller θ′(t) is. To explore paths with the same length in three kinds of networks, random walkers need least effort in SWW networks, most effort in BA networks and moderate effort in ER networks.