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Distributed Multiple-Message Broadcast in Wireless Ad-Hoc Networks under the SINR Model

  • Dongxiao Yu
  • Qiang-Sheng Hua
  • Yuexuan Wang
  • Haisheng Tan
  • Francis C. M. Lau
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7355)

Abstract

In a multiple-message broadcast, an arbitrary number of messages originate at arbitrary nodes in the network at arbitrary times. The problem is to disseminate all these messages to the whole network. This paper gives the first randomized distributed multiple-message broadcast algorithm with worst-case performance guarantee in wireless ad-hoc networks employing the SINR interference model which takes interferences from all the nodes in the network into account. The network model used in this paper also considers the harsh characteristics of wireless ad-hoc networks: there is no prior structure, and nodes cannot perform collision detection and have little knowledge of the network topology. Under all these restrictions, our proposed randomized distributed multiple-message broadcast protocol can deliver any message m to all nodes in the network in O(D + k + log2 n) timeslots with high probability, where D is the network diameter, k is the number of messages whose broadcasts overlap with m, and n is the number of nodes in the network. We also study the lower bound for randomized distributed multiple-message broadcast protocols. In particular, we prove that any uniform randomized algorithm needs \(\Omega(D+k+\frac{\log^2n}{\log\log\log n})\) timeslots to deliver k messages initially stored at k nodes to all nodes in the network.

Keywords

Collision Detection Transmission Probability Successful Transmission Interference Model Communication Graph 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Dongxiao Yu
    • 1
  • Qiang-Sheng Hua
    • 2
  • Yuexuan Wang
    • 2
  • Haisheng Tan
    • 2
  • Francis C. M. Lau
    • 1
  1. 1.Department of Computer ScienceThe University of Hong KongHong KongP.R. China
  2. 2.Institute for Interdisciplinary Information SciencesTsinghua UniversityBeijingP.R. China

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