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Two-terminal reliability analyses for a mobile ad hoc wireless network

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

Abstract

Reliability is one of the most important performance measures for emerging technologies. For these systems, shortcomings are often overlooked in early releases as the cutting edge technology overshadows a fragile design. Currently, the proliferation of the mobile ad hoc wireless networks (MAWN) is moving from cutting edge to commodity and thus, reliable performance will be expected. Generally, ad hoc networking is applied for the flexibility and mobility it provides. As a result, military and first responders employ this network scheme and the reliability of the network becomes paramount. To ensure reliability is achieved, one must first be able to analyze and calculate the reliability of the MAWN. This work describes the unique attributes of the MAWN and how the classical analysis of network reliability, where the network configuration is known a priori, can be adjusted to model and analyze this type of network. The methods developed acknowledge the dynamic and scalable nature of the MAWN along with its absence of infrastructure. Thus, the methods rely on a modeling approach that considers the probabilistic formation of different network configurations in a MAWN. Hence, this paper proposes reliability analysis methods that consider the effect of node mobility and the continuous changes in the network's connectivity.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:reensy:v:92:y:2007:i:6:p:821-829
    DOI: 10.1016/j.ress.2006.04.021
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    References listed on IDEAS

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    1. Dipesh J. Patel & Rajan Batta & Rakesh Nagi, 2005. "Clustering Sensors in Wireless Ad Hoc Networks Operating in a Threat Environment," Operations Research, INFORMS, vol. 53(3), pages 432-442, June.
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    Cited by:

    1. Chakraborty, Suparna & Goyal, N.K. & Mahapatra, S. & Soh, Sieteng, 2020. "A Monte-Carlo Markov chain approach for coverage-area reliability of mobile wireless sensor networks with multistate nodes," Reliability Engineering and System Safety, Elsevier, vol. 193(C).
    2. 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.
    3. Rocco S, Claudio M. & Ramirez-Marquez, José Emmanuel, 2009. "Deterministic network interdiction optimization via an evolutionary approach," Reliability Engineering and System Safety, Elsevier, vol. 94(2), pages 568-576.
    4. Forghani-elahabad, Majid & Mahdavi-Amiri, Nezam, 2015. "An efficient algorithm for the multi-state two separate minimal paths reliability problem with budget constraint," Reliability Engineering and System Safety, Elsevier, vol. 142(C), pages 472-481.
    5. Cook, Jason L. & Ramirez-Marquez, Jose Emmanuel, 2008. "Reliability analysis of cluster-based ad-hoc networks," Reliability Engineering and System Safety, Elsevier, vol. 93(10), pages 1512-1522.
    6. Xu, Bei & Liu, Tao & Bai, Guanghan & Tao, Junyong & Zhang, Yun-an & Fang, Yining, 2022. "A multistate network approach for reliability evaluation of unmanned swarms by considering information exchange capacity," Reliability Engineering and System Safety, Elsevier, vol. 219(C).
    7. Chen, Binchao & Phillips, Aaron & Matis, Timothy I., 2012. "Two-terminal reliability of a mobile ad hoc network under the asymptotic spatial distribution of the random waypoint model," Reliability Engineering and System Safety, Elsevier, vol. 106(C), pages 72-79.
    8. Stern, R.E. & Song, J. & Work, D.B., 2017. "Accelerated Monte Carlo system reliability analysis through machine-learning-based surrogate models of network connectivity," Reliability Engineering and System Safety, Elsevier, vol. 164(C), pages 1-9.
    9. Ramirez-Marquez, José Emmanuel & Rocco, Claudio M., 2008. "All-terminal network reliability optimization via probabilistic solution discovery," Reliability Engineering and System Safety, Elsevier, vol. 93(11), pages 1689-1697.
    10. Radislav Vaisman & Ofer Strichman & Ilya Gertsbakh, 2015. "Model Counting of Monotone Conjunctive Normal Form Formulas with Spectra," INFORMS Journal on Computing, INFORMS, vol. 27(2), pages 406-415, May.
    11. Amit Dua & Neeraj Kumar & Seema Bawa, 2017. "ReIDD: reliability-aware intelligent data dissemination protocol for broadcast storm problem in vehicular ad hoc networks," Telecommunication Systems: Modelling, Analysis, Design and Management, Springer, vol. 64(3), pages 439-458, March.
    12. Padmavathy, N. & Chaturvedi, Sanjay K., 2013. "Evaluation of mobile ad hoc network reliability using propagation-based link reliability model," Reliability Engineering and System Safety, Elsevier, vol. 115(C), pages 1-9.
    13. 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.
    14. 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.
    15. 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.
    16. Jane, Chin-Chia & Shen, Wu-Hsien & Laih, Yih-Wenn, 2009. "Practical sequential bounds for approximating two-terminal reliability," European Journal of Operational Research, Elsevier, vol. 195(2), pages 427-441, June.

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