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Optimal design of cluster-based ad-hoc networks using probabilistic solution discovery

Author

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  • Cook, Jason L.
  • Ramirez-Marquez, Jose Emmanuel

Abstract

The reliability of ad-hoc networks is gaining popularity in two areas: as a topic of academic interest and as a key performance parameter for defense systems employing this type of network. The ad-hoc network is dynamic and scalable and these descriptions are what attract its users. However, these descriptions are also synonymous for undefined and unpredictable when considering the impacts to the reliability of the system. The configuration of an ad-hoc network changes continuously and this fact implies that no single mathematical expression or graphical depiction can describe the system reliability-wise. Previous research has used mobility and stochastic models to address this challenge successfully. In this paper, the authors leverage the stochastic approach and build upon it a probabilistic solution discovery (PSD) algorithm to optimize the topology for a cluster-based mobile ad-hoc wireless network (MAWN). Specifically, the membership of nodes within the back-bone network or networks will be assigned in such as way as to maximize reliability subject to a constraint on cost. The constraint may also be considered as a non-monetary cost, such as weight, volume, power, or the like. When a cost is assigned to each component, a maximum cost threshold is assigned to the network, and the method is run; the result is an optimized allocation of the radios enabling back-bone network(s) to provide the most reliable network possible without exceeding the allowable cost. The method is intended for use directly as part of the architectural design process of a cluster-based MAWN to efficiently determine an optimal or near-optimal design solution. It is capable of optimizing the topology based upon all-terminal reliability (ATR), all-operating terminal reliability (AoTR), or two-terminal reliability (2TR).

Suggested Citation

  • Cook, Jason L. & Ramirez-Marquez, Jose Emmanuel, 2009. "Optimal design of cluster-based ad-hoc networks using probabilistic solution discovery," Reliability Engineering and System Safety, Elsevier, vol. 94(2), pages 218-228.
  • Handle: RePEc:eee:reensy:v:94:y:2009:i:2:p:218-228
    DOI: 10.1016/j.ress.2008.02.015
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    References listed on IDEAS

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    1. George S. Fishman, 1986. "A Monte Carlo Sampling Plan for Estimating Network Reliability," Operations Research, INFORMS, vol. 34(4), pages 581-594, August.
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    3. Cook, Jason L. & Ramirez-Marquez, Jose Emmanuel, 2007. "Two-terminal reliability analyses for a mobile ad hoc wireless network," Reliability Engineering and System Safety, Elsevier, vol. 92(6), pages 821-829.
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    6. J. L. Cook & J. E. Ramirez-Marquez, 2007. "Reliability of capacitated mobile ad hoc networks," Journal of Risk and Reliability, , vol. 221(4), pages 307-318, December.
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    Cited by:

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    2. A Carrigy & J E Ramirez-Marquez & C M Rocco, 2010. "Multistate stochastic network interdiction via reliability modelling and evolutionary optimization," Journal of Risk and Reliability, , vol. 224(1), pages 27-42, March.
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    5. Gaurav Khanna & S. K. Chaturvedi & Sieteng Soh, 2019. "Reliability evaluation of mobile ad hoc networks by considering link expiration time and border time," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 10(3), pages 399-415, June.
    6. Xiang, Shihu & Yang, Jun, 2023. "A novel adaptive deployment method for the single-target tracking of mobile wireless sensor networks," Reliability Engineering and System Safety, Elsevier, vol. 234(C).
    7. Xiang, Shihu & Yang, Jun, 2018. "Performance reliability evaluation for mobile ad hoc networks," Reliability Engineering and System Safety, Elsevier, vol. 169(C), pages 32-39.
    8. Rocco S., Claudio M. & Emmanuel Ramirez-Marquez, José & Salazar A., Daniel E., 2010. "Bi and tri-objective optimization in the deterministic network interdiction problem," Reliability Engineering and System Safety, Elsevier, vol. 95(8), pages 887-896.
    9. Guimarães, Almir P. & Maciel, Paulo R.M. & Matias, Rivalino, 2013. "An analytical modeling framework to evaluate converged networks through business-oriented metrics," Reliability Engineering and System Safety, Elsevier, vol. 118(C), pages 81-92.

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