Reliability Analysis of k-out-of-n Systems of Components with Potentially Brittle Behavior by Universal Generating Function and Linear Programming

Due to initial cracks, careless construction, and extreme load conditions, components with brittle behavior may exist in a structural system. The presence of brittle behavior of components usually is accompanied by a low strength. However, existing methods for calculating the reliability of structures of components with brittle behavior are rather complicated or impossible. By means of decomposing the entire system into a set of subsystems, this paper proposed a method to estimate the bounds on failure probability of k-out-of-n system of components with potentially brittle behavior by using universal generating function (UGF) and linear programming (LP). Based on the individual component state probabilities and joint probabilities of the states of a small number of components, the proposed method can provide the bounds for the failure probability of a system with a large number of components. The accuracy and efficiency of the proposed method are investigated using numerical examples.

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Backward Recursive Method for Structural Reliability Calculation Based on the Universal Generating Function

IEEE Transactions on Reliability ◽

10.1109/tr.2020.3047415 ◽

2021 ◽

pp. 1-10

Author(s):

Jinyu Zhou ◽

Liyang Xie ◽

Wenqin Han

Keyword(s):

Generating Function ◽

Structural Reliability ◽

Recursive Method ◽

Reliability Calculation ◽

Universal Generating Function

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A Fast Optimization Method for Reliability and Performance of Cloud Services Composition Application

Journal of Applied Mathematics ◽

10.1155/2013/407267 ◽

2013 ◽

Vol 2013 ◽

pp. 1-12 ◽

Cited By ~ 2

Author(s):

Zhao Wu ◽

Naixue Xiong ◽

Yannong Huang ◽

Qiong Gu ◽

Chunyang Hu ◽

...

Keyword(s):

Cloud Computing ◽

State Space ◽

Generating Function ◽

Performance Optimization ◽

Optimization Method ◽

Cloud Services ◽

Services Composition ◽

Fast Optimization ◽

And Performance ◽

Universal Generating Function

At present the cloud computing is one of the newest trends of distributed computation, which is propelling another important revolution of software industry. The cloud services composition is one of the key techniques in software development. The optimization for reliability and performance of cloud services composition application, which is a typical stochastic optimization problem, is confronted with severe challenges due to its randomness and long transaction, as well as the characteristics of the cloud computing resources such as openness and dynamic. The traditional reliability and performance optimization techniques, for example, Markov model and state space analysis and so forth, have some defects such as being too time consuming and easy to cause state space explosion and unsatisfied the assumptions of component execution independence. To overcome these defects, we propose a fast optimization method for reliability and performance of cloud services composition application based on universal generating function and genetic algorithm in this paper. At first, a reliability and performance model for cloud service composition application based on the multiple state system theory is presented. Then the reliability and performance definition based on universal generating function is proposed. Based on this, a fast reliability and performance optimization algorithm is presented. In the end, the illustrative examples are given.

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