scholarly journals Influence of Load on Reliability of Storage Area Networks

2021 ◽  
Vol 6 (6) ◽  
pp. 1533-1552
Author(s):  
Guixiang Lv ◽  
Liudong Xing
Keyword(s):  
Data Storage ◽  
Proportional Hazards Model ◽  
Failure Time ◽  
Data Access ◽  
Accelerated Failure Time Model ◽  
Cascading Failures ◽  
Time Model ◽  
Storage Area Networks ◽  
Storage Area ◽  
Data Loading

During the coronavirus pandemic, telecommuting is widely required, making remote data access grow significantly. This requires highly reliable data storage solutions. Storage area networks (SANs) are one of such solutions. To guarantee that SANs can deliver the desired quality of service, cascading failures must be prevented, which occur when a single initial incident triggers a cascade of unexpected failures of other devices. One such incident is the data loading/overloading, causing the malfunction of one device and further cascading failures. Thus, it is crucial to address influence of data loading on the SAN reliability modeling and analysis. In this work, we make contributions by modeling the effects of data loading on the reliability of an individual switch device in SANs though the proportional-hazards model and accelerated failure-time model. Effects of loading on the reliability of the entire SAN are further investigated through dynamic fault trees and binary decision diagrams-based analysis of a mesh SAN system.

CEO Overconfidence and the Timeliness of Goodwill Impairments

2020 ◽  
Author(s):  
Paul Hribar ◽  
Byung Hun Chung
Keyword(s):  
Proportional Hazards ◽  
Proportional Hazards Model ◽  
Failure Time ◽  
Cox Proportional Hazards ◽  
Cox Proportional Hazards Model ◽  
Accelerated Failure Time Model ◽  
Time Model ◽  
Cross Sectional ◽  
Future Performance ◽  
Hazards Model

We use survival analysis techniques to examine whether overconfidence affects the likelihood and timeliness of goodwill impairments. We predict that overconfident CEOs have a lower likelihood of impairment in any firm quarter, and take longer, on average, to impair goodwill. Using the Cox proportional-hazards model and the accelerated failure time model, we find evidence consistent with both predictions. In cross sectional tests, we find having more financial experts on the board mitigates the effect of CEO overconfidence on the timeliness of goodwill impairments, while uncertainty in predicting a firm's future performance strengthens the effect. Additional results show that overconfident CEOs hold overly optimistic expectations of their firms' performance, and that they underweight negative market signals prior to the impairment decisions.

scholarly journals Applications of Survival Analysis in Botanical Epidemiology

2004 ◽  
Vol 94 (9) ◽  
pp. 1022-1026 ◽  
Author(s):  
H. Scherm ◽  
P. S. Ojiambo
Keyword(s):  
Survival Analysis ◽  
Proportional Hazards Model ◽  
Failure Time ◽  
Disease Onset ◽  
Field Analysis ◽  
Accelerated Failure Time Model ◽  
Accelerated Failure Time ◽  
Time Model ◽  
Accelerated Failure ◽  
Failure Time Model

Data on the occurrence and timing of discrete events such as spore germination, disease onset, or propagule death are recorded commonly in epidemiological studies. When analyzing such “time-to-event” data, survival analysis is superior to conventional statistical techniques because it can accommodate censored observations, i.e., cases in which the event has not occurred by the end of the study. Central to survival analysis are two mathematical functions, the survivor function, which describes the probability that an individual will “survive” (i.e., that the event will not occur) until a given point in time, and the hazard function, which gives the instantaneous risk that the event will occur at that time, given that it has not occurred previously. These functions can be compared among two or more groups using chi-square-based test statistics. The effects of discrete or continuous covariates on survival times can be quantified with two types of models, the accelerated failure time model and the proportional hazards model. When applied to longitudinal data on the timing of defoliation of individual blueberry leaves in the field, analysis with the accelerated failure time model revealed a significantly (P < 0.0001) increased defoliation risk due to Septoria leaf spot, caused by Septoria albopunctata. Defoliation occurred earlier for lower leaves than for upper leaves, but this effect was confounded in part with increased disease severity on lower leaves.

Dependability Analysis of Homogeneous Distributed Software/Hardware Systems

2015 ◽  
Vol 22 (02) ◽  
pp. 1550007
Author(s):  
G. Vijayalakshmi
Keyword(s):  
Reliability Analysis ◽  
Distributed System ◽  
Failure Time ◽  
Load Sharing ◽  
Accelerated Failure Time Model ◽  
Time To Failure ◽  
Critical Systems ◽  
Time Model ◽  
Distributed Software ◽  
Dependability Analysis

With the increasing demand for high availability in safety-critical systems such as banking systems, military systems, nuclear systems, aircraft systems to mention a few, reliability analysis of distributed software/hardware systems continue to be the focus of most researchers. The reliability analysis of a homogeneous distributed software/hardware system (HDSHS) with k-out-of-n : G configuration and no load-sharing nodes is analyzed. However, in practice the system load is shared among the working nodes in a distributed system. In this paper, the dependability analysis of a HDSHS with load-sharing nodes is presented. This distributed system has a load-sharing k-out-of-(n + m) : G configuration. A Markov model for HDSHS is developed. The failure time distribution of the hardware is represented by the accelerated failure time model. The software faults are detected during software testing and removed upon failure. The Jelinski–Moranda software reliability model is used. The maintenance personal can repair the system up on both software and hardware failure. The dependability measures such as reliability, availability and mean time to failure are obtained. The effect of load-sharing hosts on system hazard function and system reliability is presented. Furthermore, an availability comparison of our results and the results in the literature is presented.

Sign in / Sign up

Export Citation Format

Share Document