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Reliability Analysis of Correlated Competitive and Dependent Components Considering Random Isolation Times

Shuo Cai1, Tingyu Luo1, Fei Yu1,*, Pradip Kumar Sharma2, Weizheng Wang1, Lairong Yin3

1 School of Computer and Communication Engineering, Changsha University of Science and Technology, Changsha, 410114, China
2 Department of Computing Science, University of Aberdeen, Aberdeen, UK
3 School of Automotive and Mechanical Engineering, Changsha University of Science and Technology, Changsha, 410114, China

* Corresponding Author: Fei Yu. Email: email

Computers, Materials & Continua 2023, 76(3), 2763-2777.


In the Internet of Things (IoT) system, relay communication is widely used to solve the problem of energy loss in long-distance transmission and improve transmission efficiency. In Body Sensor Network (BSN) systems, biosensors communicate with receiving devices through relay nodes to improve their limited energy efficiency. When the relay node fails, the biosensor can communicate directly with the receiving device by releasing more transmitting power. However, if the remaining battery power of the biosensor is insufficient to enable it to communicate directly with the receiving device, the biosensor will be isolated by the system. Therefore, a new combinatorial analysis method is proposed to analyze the influence of random isolation time (RIT) on system reliability, and the competition relationship between biosensor isolation and propagation failure is considered. This approach inherits the advantages of common combinatorial algorithms and provides a new approach to effectively address the impact of RIT on system reliability in IoT systems, which are affected by competing failures. Finally, the method is applied to the BSN system, and the effect of RIT on the system reliability is analyzed in detail.


Cite This Article

S. Cai, T. Luo, F. Yu, P. K. Sharma, W. Wang et al., "Reliability analysis of correlated competitive and dependent components considering random isolation times," Computers, Materials & Continua, vol. 76, no.3, pp. 2763–2777, 2023.

cc This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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