Testability Distributed Real-Time Computing System

Author(s):  
A.M. Gruzlikov ◽  
N.V. Kolesov
10.1114/1.185 ◽  
1999 ◽  
Vol 27 (2) ◽  
pp. 180-186 ◽  
Author(s):  
David J. Christini ◽  
Kenneth M. Stein ◽  
Steven M. Markowitz ◽  
Bruce B. Lerman

Author(s):  
Junjun Zheng ◽  
Hiroyuki Okamura ◽  
Tadashi Dohi

Component importance analysis is to measure the effect on system reliability of component reliabilities, and is used to the system design from the reliability point of view. On the other hand, to guarantee high reliability of real-time computing systems, redundancy has been widely applied, which plays an important role in enhancing system reliability. One of commonly used type of redundancy is the standby redundancy. However, redundancy increases not only the complexity of a system but also the complexity of associated problems such as common-mode error. In this paper, we consider the component importance analysis of a real-time computing system with warm standby redundancy in the presence of Common-Cause Failures (CCFs). Although the CCFs are known as a risk factor of degradation of system reliability, it is difficult to evaluate the component importance measures in the presence of CCFs analytically. This paper introduces a Continuous-Time Markov Chain (CTMC) model for real-time computing system, and applies the CTMC-based component-wise sensitivity analysis which can evaluate the component importance measures without any structure function of system. In numerical experiments, we evaluate the effect of CCFs by the comparison of system performance measure and component importance in the case of system without CCF with those in the case of system with CCFs. Also, we compare the effect of CCFs on the system in warm and hot standby configurations.


2021 ◽  
Vol 2131 (3) ◽  
pp. 032036
Author(s):  
M A Koshelev ◽  
D B Borzov

Abstract This paper is devoted to real time reconfigurable computing systems. The theme of research study of speed of algorithm’s work with different parameters of the system and search of optimum parameters. The aim of the study is to check the dependence of the speed of the algorithm reconfigurable real-time computing system, depending on the volume of data being transmitted. The study was conducted using min-max methods, by trying the number of processors and the volume of data transferred to find the best option out of the presented ones. A pattern was found, how the time gain varied with increasing data volume and at which parameters it reached the highest performance.


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