A network business availability modeling method based on Markov chain-Reference-Cited by-同舟云学术

A network business availability modeling method based on Markov chain

Published:2022-08-19 Issue:1 Volume:2022 Page:
ISSN:1687-1499
Container-title:EURASIP Journal on Wireless Communications and Networking
language:en
Short-container-title:J Wireless Com Network

Author:

Lu Ying,Chen Yusi,Liu Jin,Fu Yanfang^ORCID,Guo Qi,Fan Nierui

Abstract

AbstractMilitary tactical networks (MTNs) have grown in size and complexity as the volume of battlefield communications business has increased dramatically. There is a critical need for a quantitative evaluation method to assess the performance of MTNs. Based on the transmission characters of battlefield communication business and the availability of communication equipment, this paper proposed a Markov chain-based network steady-state availability model. Using this model and the analysis of the CSMA/CA transmission protocol as preconditions, a delay-based quantitative evaluation model of network business availability is proposed based on statistical principles. The relationship between network business availability and crucial metrics such as node size and node failure/repair ratio is investigated in simulation experiments to ensure the validity and correctness of the proposed model. The work done in this paper contributes to effectively evaluating the overall availability of MTNs in a complex environment.

Funder

Shaanxi Provincial Science and Technology Department

Publisher

Springer Science and Business Media LLC

Subject

Computer Networks and Communications,Computer Science Applications,Signal Processing

Link

https://link.springer.com/content/pdf/10.1186/s13638-022-02154-y.pdf

Reference27 articles.

1. A. Nt, A. Cs, A. Cg, B. Vva, A survey on mobility in wireless sensor networks. Science 2, 889 (2021)

2. H. Zhou, T. Wu, H. Zhang, J. Wu, Incentive-driven deep reinforcement learning for content caching and d2d offloading. IEEE J Sel Areas Commun 99, 1–1 (2021)

3. W.C. Yeh, Y.C. Lin, Y.Y. Chung, M. Chih, A particle swarm optimization approach based on monte carlo simulation for solving the complex network reliability problem. IEEE Trans Reliab 59(1), 212–221 (2010)

4. M. Herlich, C. Maier, Measuring and monitoring reliability of wireless networks. IEEE Commun Mag 59(1), 5568 (2021)

5. C.M. Lin, H.K. Teng, C.C. Yang, H.L. Weng, C.C. Chung, A mesh network reliability analysis using reliability block diagram. IEEE 2, 778 (2010)

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Availability Markov Models of Complex Equipment with Relearning Diagnostic Means after Detecting Latent Failures;2023 13th International Conference on Dependable Systems, Services and Technologies (DESSERT);2023-10-13