Acknowledgement
This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government(MSIT) (No. NRF-2019R1F1A1060743).
References
- A. Alsaaidah, M. Zalisham, M. Fadzli, and H. Abdel-Jaber, Markov-modulated Bernoulli-based performance analysis for gentle BLUE and BLUE algorithms under bursty and correlated traffic, J. Comput. Sci. 12 (2016), no. 6, 289-299. https://doi.org/10.3844/jcssp.2016.289.299
- A. Arulmurugan and A. Amuthan, Markov modulated Bernoulli prediction process-based cluster head selection mechanism for improving resilience in wireless sensor networks, Int. J. Commun. Syst. 34 (2021), no. 8, e4771. https://doi.org/10.1002/dac.4771
- E. Cinlar, Introduction to Stochastic Processes, Courier Corporation, Prentice Hall, New Jersey, 1975.
- A. Duque, R. Stanica, H. Rivano, and A. Desportes, Analytical and simulation tools for optical camera communications, Comput. Commun. 160 (2020), 52-62. https://doi.org/10.1016/j.comcom.2020.05.036
- L. Guan, I. U. Awan, M. E. Woodward, and X. Wang, Discrete-time performance analysis of a congestion control mechanism based on RED under multi-class bursty and correlated traffic, J. Syst. Softw. 80 (2007), no. 10, 1716-1725. https://doi.org/10.1016/j.jss.2006.12.549
- L. Hogben, Handbook of Linear Algebra, CRC Press, Boca Raton, 2013.
- B. Hu and T. A. Tamba, Optimal codesign of industrial networked control systems with state-dependent correlated fading channels, Internat. J. Robust Nonlinear Control 29 (2019), no. 13, 4472-4493. https://doi.org/10.1002/rnc.4643
- B. Hu, Y. Wang, P. V. Orlik, T. Koike-Akino, and J. Guo, Co-design of safe and efficient networked control systems in factory automation with state-dependent wireless fading channels, Automatica J. IFAC 105 (2019), 334-346. https://doi.org/10.1016/j.automatica.2019.04.009
- G. Joseph and P. K. Varshney, State estimation of linear systems with sparse inputs and Markov-modulated missing outputs, Proceedings of 30th European Signal Processing Conference, Belgrade, Serbia, (2022), 837-841. https://doi.org/10.23919/EUSIPCO55093.2022.9909657
- B. Khamidehi, M. Raeis, and E. S. Sousa, Dynamic resource management for providing QoS in drone delivery systems, Proceedings of IEEE 25th International Conference on Intelligent Transportation Systems, Macau, China, (2022), 3529-3536. https://doi.org/10.1109/ITSC55140.2022.9922133
- Y. Kim, Starvation analysis of CDF-based scheduling over Nakagami-m Markov fading channels, IEEE Commun. Lett. 22 (2018), no. 2, 372-375. https://doi.org/10.1109/LCOMM.2017.2765308
- V. G. Kulkarni, Modeling and Analysis of Stochastic Systems, CRC Press, Boca Raton, 2016.
- L. B. Lim, L. Guan, A. Grigg, I. W. Phillips, X. G. Wang, and I. U. Awan, RED and WRED performance analysis based on superposition of N MMBP arrival process, Proceedings of 24th IEEE International Conference on Advanced Information Networking and Applications, Perth, WA, Australia, (2010), 66-73. https://doi.org/10.1109/AINA.2010.85
- L. M. Maillart, C. R. Cassady, and J. Honeycutt, A binomial approximation of lot yield under Markov modulated Bernoulli item yield, IIE Trans. 40 (2008), no. 4, 459-467. https://doi.org/10.1080/07408170701592507
- S. Ozekici, Markov modulated Bernoulli process, Math. Methods Oper. Res. 45 (1997), no. 3, 311-324. https://doi.org/10.1007/BF01194782
- S. Ozekici and R. Soyer, Bayesian analysis of Markov modulated Bernoulli processes, Math. Methods Oper. Res. 57 (2003), no. 1, 125-140. https://doi.org/10.1007/s001860200268
- S. Ozekici and R. Soyer, Network reliability assessment in a random environment, Naval Res. Logist. 50 (2003), no. 6, 574-591. https://doi.org/10.1002/nav.10072
- S. Ozekici and R. Soyer, Reliability Modeling and Analysis in Random Environments, Mathematical Reliability: An Expository Perspective, Springer, Boston, MA, 2004. https://doi.org/10.1007/978-1-4419-9021-1_13
- N. Privault, Stochastic analysis of Bernoulli processes, Probab. Surv. 5 (2008), 435-483. https://doi.org/10.1214/08-PS139
- P. Sadeghi, R. A. Kennedy, P. B. Rapajic, and R. Shams, Finite-state Markov modeling of fading channels-a survey of principles and applications, IEEE Signal Process. Mag. 25 (2008), no. 5, 57-80. https://doi.org/10.1109/MSP.2008.926683
- H. SHI, R. V. Prasad, E. Onur, and I. G. M. M. Niemegeers, Fairness in wireless networks: issues, measures and challenges, IEEE Commun. Surv. Tutor. 16 (2014), no. 1, 5-24. https://doi.org/10.1109/SURV.2013.050113.00015
- Y. Sun, X. Chi, B. Yu, S. Zhao, S. Li, and Q. Meng, Hop-by-hop bandwidth allocation and deployment for SFC with end-to-end delay QoS guarantees, Comput. Commun. 192 (2022), 256-267. https://doi.org/10.1016/j.comcom.2022.06.002
- B. Tomlin, Impact of supply learning when suppliers are unreliable, Manuf. Serv. Oper. Manag. 11 (2009), no. 2, 192-209. https://doi.org/10.1287/msom.1070.0206
- Q. Xu, S. Li, T. V. Do, K. Jia, and N. Yang, Performance analysis of cognitive radio networks with burst dynamics, IEEE Access 9 (2021), 110627-110638. https://doi.org/10.1109/ACCESS.2021.3103321
- B. Yu, X. Chi, and H. Sun, Delay analysis for aggregate traffic based on martingales theory, IET Commun. 14 (2020), no. 5, 760-767. https://doi.org/10.1049/iet-com.2019.0282