Backup path allocation based on a correlated link failure probability model in overlay networks

Author(s):  
Weidong Cui ◽  
I. Stoica ◽  
R.H. Katz
Author(s):  
Mohammad Amin Hariri-Ardebili

Risk analysis of concrete dams and quantification of the failure probability are important tasks in dam safety assessment. The conditional probability of demand and capacity is usually estimated by numerical simulation and Monte Carlo technique. However, the estimated failure probability (or the reliability index) is dam-dependent which makes its application limited to some case studies. This article proposes an analytical failure model for generic gravity dam classes which is optimized based on large number of nonlinear finite element analyses. A hybrid parametric–probabilistic–statistical approach is used to estimate the failure probability as a function of dam size, material distributional models and external hydrological hazard. The proposed model can be used for preliminary design and evaluation of two-dimensional gravity dam models.


Author(s):  
Faiz-ul Hassan ◽  
Wim Vanderbauwhede ◽  
Fernando Rodríguez-Salazar

On-chip communication is becoming an important bottleneck in the design and operation of high performance systems where it has to face additional challenges due to device variability. Communication structures such as tapered buffer drivers, interconnects, repeaters, and data storage elements are vulnerable to variability, which can limit the performance of the on-chip communication networks. In this regard, it becomes important to have a complete understanding of the impact that variability will have on the performance of these circuit elements in order to design high yield and reliable systems. In this paper, the authors have characterized the performance of the communication structures under the impact of random dopant fluctuation (RDF) for the future technology generations of 25, 18, and 13 nm. For accurate characterization of their performance, a Monte Carlo simulation method has been used along with predictive device models for the given technologies. Analytical models have been developed for the link failure probability of a repeater inserted interconnect which uses characterization data of all communication structures to give an accurate prediction of the link failure probability. The model has also been extended to calculate the link failure probability of a wider communication link.


2013 ◽  
Vol 336-338 ◽  
pp. 471-474
Author(s):  
Shi Guang ◽  
Hai Jing Yang ◽  
Qi Wei Wang ◽  
Yan Jin

In allusion to the issues of system line state transfer that may arise in adverse weather, a new method of probability calculation is proposed. In a statistical analysis, this article firstly defines that failure probability of the first line subjects to Poisson distribution. Secondly, we figure out the power flow transferring distribution after first line fault, according to the method of Flow Transferring Relativity Factor (FTRF), and combine with the protective possibility so as to build the probability model between the load rate and protection action. Then, the method defines the severity of line load rate. Finally, the approach constructs the line state transition probability model considering direct and indirect factors in adverse weather. The effectiveness and correctness of the proposed method are verified by simulation based on IEEE 39-node system.


2015 ◽  
Vol 31 (2) ◽  
pp. 217-227
Author(s):  
Yaofang Li ◽  
Jie Xiao ◽  
Bin Wu ◽  
Hong Wen ◽  
Hongfang Yu ◽  
...  

Author(s):  
LIYANG XIE ◽  
JINYU ZHOU ◽  
XIAOFANG YANG ◽  
MINGCHUAN ZHANG

Since multiple-failure event can destroy the safety policy of redundancy, accurate prediction of multiple-failure probability is of great importance. However, the statistical dependence between component failures might lead to unrealistic estimation of the conventional system failure probability model since it is valid only in the situation of independent component failures. On the other hand, the lack of multiple-failure event data makes the statistical estimation of multiple-failure probability suffer serious uncertainty. General failure event data experienced by other systems might be the only data available to estimate the system under study. In order to evaluate the target system in such a situation, an appropriate approach is highly required by which the right information can be mined from the operating experience of reference systems. Based on the multiple-failure information contained in load-strength interference relationship, this paper presents an approach to estimate multiple-failure probability of dependent k-out-of-n system according to failure event data available. The data may come from the operating experience of the system to be evaluated or reference systems with similar load-strength interference relationships. As examples, the failure probabilities of emergency diesel generator groups are estimated according to the multiple-failure event data of reference groups of different sizes. The estimation results are consistent well with the operating records.


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