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A Double Pulse Control Strategy for Misinformation Propagation in Human Mobile Opportunistic Networks

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Book cover Wireless Algorithms, Systems, and Applications (WASA 2015)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 9204))

Abstract

Mobile Opportunistic Networks (MONs) are effective solutions to uphold communications in the situations where traditional communication networks are unavailable. However, MONs can be abused to disseminate misinformation causing undesirable effects in public. To prevent misinformation from propagating, we first propose a formal model to formulate the process of misinformation propagation based on the ordinary differential equation. Secondly, we explore a general framework to describe the random mobility of nodes, and derive a new contact rate between nodes. Thirdly, we propose a double pulse control strategy of vaccination and treatment for inhibiting misinformation propagation. Moreover, a novel pulse control model of misinformation propagation is developed based on the impulsive differential equation. Finally, through the derivation and stability analysis of a misinformation-free period solution of the proposed model, we obtain a threshold upon which misinformation dies out. The simulation results validate our theoretical analysis.

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Acknowledgment

This work is supported by the Natural Science Foundation of China (Grant Nos. 61373083, 61402273), and the Program of Key Science and Technology Innovation Team in Shaanxi Province (No. 2014KTC-18).

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Correspondence to Xiaoming Wang .

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© 2015 Springer International Publishing Switzerland

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Wang, X., Lin, Y., Zhang, L., Cai, Z. (2015). A Double Pulse Control Strategy for Misinformation Propagation in Human Mobile Opportunistic Networks. In: Xu, K., Zhu, H. (eds) Wireless Algorithms, Systems, and Applications. WASA 2015. Lecture Notes in Computer Science(), vol 9204. Springer, Cham. https://doi.org/10.1007/978-3-319-21837-3_56

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  • DOI: https://doi.org/10.1007/978-3-319-21837-3_56

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-21836-6

  • Online ISBN: 978-3-319-21837-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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