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(Q, S)-distance model and counting algorithms in dynamic distributed systems

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  • Zhiwei Yang
  • Weigang Wu
  • Yishun Chen
  • Xiaola Lin
  • Jiannong Cao

Abstract

With the advance in mobile network-based systems, dynamic system has become one of the hotspots in fundamental study of distributed systems. In this article, we consider the dynamic system with frequent topology changes arising from node mobility or other reasons, which is also referred to as “dynamic network.†With the model of dynamic network, fundamental distributed computing problems, such as information dissemination and election, can be formally studied with rigorous correctness. Our work focuses on the node counting problem in dynamic environments. We first define two new dynamicity models, named ( Q, S )- distance and ( Q, S )*- distance , which describe dynamic changes of information propagation time against topology changes. Based on these two models, we design three different counting algorithms which basically adopt the approach of diffusing computation. These algorithms mainly differ in communication cost due to different information collection procedures. The correctness of all the algorithms is formally proved and their performance is evaluated via both theoretical analysis and experimental simulations.

Suggested Citation

  • Zhiwei Yang & Weigang Wu & Yishun Chen & Xiaola Lin & Jiannong Cao, 2018. "(Q, S)-distance model and counting algorithms in dynamic distributed systems," International Journal of Distributed Sensor Networks, , vol. 14(1), pages 15501477187, January.
    • Handle: RePEc:sae:intdis:v:14:y:2018:i:1:p:1550147718756872
    DOI: 10.1177/1550147718756872
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    References listed on IDEAS

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    1. Catherine Matias & Vincent Miele, 2017. "Statistical clustering of temporal networks through a dynamic stochastic block model," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 79(4), pages 1119-1141, September.
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