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Optimal Epidemic Information Dissemination in Uncertain Dynamic Environment

Research output: Contribution to journalJournal article

Published
  • Daxin Tian
  • Ziyi Dai
  • Jianshan Zhou
  • Xuting Duan
  • Zhengguo Sheng
  • Min Chen
  • Qiang Ni
  • Victor C.m. Leung
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<mark>Journal publication date</mark>08/2018
<mark>Journal</mark>IEEE Wireless Communications Letters
Issue number4
Volume7
Number of pages4
Pages (from-to)518-521
Publication statusPublished
Early online date11/01/18
Original languageEnglish

Abstract

Optimization of stochastic epidemic information dissemination plays a significant role in enhancing the reliability of epidemic networks. This letter proposes a multi-stage decision-making optimization model for stochastic epidemic information dissemination based on dynamic programming, in which uncertainties in a dynamic environment are taken into account. We model the inherent bimodal dynamics of general epidemic mechanisms as a Markov chain, and a state transition equation is proposed based on this Markov chain. We further derive optimal policies and a theoretical closed-form expression for the maximal expected number of successfully delivered messages. The properties of the derived model are theoretically analyzed. Simulation results show an improvement in reliability, in terms of accumulative number of successfully delivered messages, of epidemic information dissemination in stochastic situations.

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©2018 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.