System Reliability Estimation Research Articles

Optimal Scheme Models with Two Kinds of Errors

In this paper, we propose stochastic scheme models with two kinds of errors for a computer system. A highly reliable computer system needs greatly to be backed up successfully in case of computer system crashes due to hardware failures and malicious software infections. We aim to determine appropriate backup times in computer processing of constant and random tasks. For this purpose, the trade-off between backup times and data losses due to errors is considered. The total execution times until the computing processing completes are obtained, and optimal backup policies to minimize them are derived analytically. Furthermore, we take up extended models of random tasks with [Formula: see text] sub-tasks and analyze them.

Research on Wireless Multimedia Big Data Transmission Model Based on Non-linear Algebraic Equation with the Adaptive Scheduling Algorithm

With the rapid development of computer technology, image processing and automatic book recognition has become a very important and practical field, and this discipline has a broad prospect and great potential. The digital vision system is a multi-plane information analysis method based on the human brain, which is applied to library identification problems by studying several regular changes in the distribution of objects themselves in two-dimensional space and three-dimensional position, in order to improve book quality and reduce costs. In addition, digital reading devices have become an essential part of people's daily learning life, and multimedia retrieval methods have also undergone radical changes, image processing is becoming more and more complex, and algorithms must become more efficient and reliable as the amount of computing increases to a certain level, so as to adapt to this fast and powerful data storage and query needs. Therefore, the trend is to improve the speed and reliability of computer systems. In this research, we provide a nonlinear model of optimal allocation employing an ant colony management strategy, a genetic operator, and an adaptive scheduling algorithm based on topology (dB) to discover the best scheduling scheme and test its feasibility via simulation. It proposes a viable idea for tackling the practical wireless multimedia massive data transmission model problem by applying the method to the real-time processing process in other sectors with high importance and resilience.

A Stochastic Analysis of Computing Models in Computer System Reliability Based on Hardware and Software

A Stochastic Analysis of Computing Models in Computer System Reliability Based on Hardware and Software

Assessment of computing systems reliability by non-parametric method by small samples of operational data

A new method for assessing the reliability of small computing systems that allows the generation of only small samples of operational data is proposed in the article. The result of applying the technique is the posterior failure distribution density, on the basis of which various reliability indicators can be calculated. The methodology consists of two stages: the first is the preparation of operational data, including detection of failures using machine learning methods, and the second is the construction of the failure distribution density using the adapted Rosenblatt–Parzen method. Increasing the efficiency of estimates using the proposed method is achieved by taking into account censored data, compensating for the shift of failure distribution densities and finding the optimal smoothing parameter.

A Markovian approach to reliability estimation of series-parallel system with Fermatean fuzzy sets

Markov process has been an extremely contributive method in the reliability evaluation of electrical systems for the past many decades, as a result, it has been extended by numerous researchers to address various types of issues occurring in different types of engineering systems. However, one thing it fails to address is the fuzziness in real-life systems. This fuzziness or randomness can occur either because of incomplete awareness of the operating conditions or the application of different numerical assessment methods by different operators, causing inconsistency in a system’s assessment. It can be dealt with the incorporation of the concept of fuzzy sets in the reliability analysis. This study aims to incorporate fuzzy sets, specifically, Fermatean fuzzy sets (FFS) with the Markov procedure for assessing the fuzzy reliability, availability, and sensitivity of fuzzy reliability of a system. The described approach is justified with an example of a generic series–parallel system and its fuzzy reliability and availability are computed by Markov modelling where failure rates are characterized by triangular Fermatean fuzzy numbers (TFFN). It is obtained that the behaviour of reliability, availability and sensitivity are the same as in conventional reliability evaluation, thus establishing that the proposed technique is valid. The parameters thus obtained are also depicted both in tabular and graphical forms to achieve conclusive results.

Reliability Analysis and Life Cycle Cost Optimization of Hydraulic Excavator

This study focuses on conducting a reliability analysis of an excavator from its field failure data and improve its reliability cost effectively. The aim of the research is to perform reliability estimation of systems and identify the critical subsystem with significant contributions to system unreliability. The reliability analysis was performed using repairable system data analysis approaches. Life cycle cost (LCC) was estimated for critical subsystems, and it was optimized to select cost effective reliability improvement strategy. The results of the study provide valuable insights into the performance and cost-effectiveness of the excavator and its subsystems, which can assist manufacturers and operators in optimizing their equipment’s reliability, availability while considering the cost implications over the life cycle of the equipment. The results show that the undercarriage has critical contributions to system unreliability. This study attempts deep down reliability analysis of critical undercarriage components for optimal selection of improvement method among feasible alternatives. LCC analysis and its optimization performed on the critical sub-system is expected to help OEM save approx. 15% of LCC. The empirical data used in the paper is based on field data gathered during the operational life of the hydraulic excavator over approx. six years in its Indian operations.

Integrated CPU Monitoring Using 2D Temperature Sensor Arrays Directly Printed on Heat Sinks

AbstractIn today's digital world, the demand for computer security and system reliability is a crucial element. Monitoring the CPU temperature during operation provides valuable insights but is currently limited to the embedded on‐chip sensors. The implementation of an extra security layer based on temperature monitoring can detect anomalies in an early stage, identify malware, and help mitigate attacks. The approach of integrating more on‐chip temperature sensors into the silicon is avoided due to space, power limitations, and cost constraints. However, the field of printed electronics and sensor technology has recently seen significant progress. This is the first work that introduces a fully‐printed temperature sensor array integrated onto the cooling unit of a CPU. It offers a novel approach for the practical implementation of such sensors into an operational computer system. The present sensor array, consisting of 396 sensor pixels, detects local hotspots induced by the underneath CPU cores, leading to an individual thermal fingerprint. This unique method paves the way for addressing pivotal elements of computer security, as deviations from expected thermal behavior can signal malicious activities. Additionally, this innovation facilitates reliability optimization. The detailed thermal map garnered provides insights into which cores are subjected to significant stress over time.

Fault Tree Analysis Including Component Dependencies

Fault Tree (FT) analysis is not only the most common technique used in engineering practice for the estimation of system reliability, but is also a key tool shared between designers, analysts, and regulators for the safe operation and licensing purposes. In spite of its long lasting success, traditional FT analysis presents significant limitations in modeling a wide range of features frequently encountered in modern systems. The most critical of these is the assumption of failure events independence, which is often not justified by the realistic behavior of the engineering system, undermining modeling accuracy. This article introduces a novel methodology for the analysis of FTs allowing for component dependencies and dynamic features. The proposed approach, based on the use of binary decision diagrams, is demonstrated using a simple numerical application for verification. Its applicability and computational feasibility is discussed in details.

Research on wireless multimedia big data transmission model based on non-linear algebraic equation with the adaptive scheduling algorithm

With the rapid development of computer technology, image processing and automatic book recognition has become a very important and practical field, and this discipline has a broad prospect and great potential. The digital visión system is a multi-plane information análisis method basad on the human brain, which is applied to library identification problems by studying several regular changes in the distribution of objects themselves in two-dimensional space and three-dimensional position, in order to improve book quality and reduce costs. In addition, digital Reading devices have become an essential part of people’s daily learning life, and multimedia retrieval methods have also undergone radical changes, image processing is becoming more and more complex, and algorithms must become more efficient and reliable as the amount of computing increases to a certain level, so as to adapt to this fast and powerful data storage and query needs. Therefore, the tren is to improve the speed and reliability of computer systems. This paper discusses and proposes measures for the analysis and extraction, classification and sorting of library images.

System reliability calculation based on the run-time analysis of ladder program

Programmable logic controller (PLC) system, a typical member in the embedded family, is now widely applied in industry. For safety critical PLC systems, reliability is of top significance. However, due to subcomponents’ temporal correlations caused by the run-time execution of embedded ladder programs, the complexity of reliability analysis is greatly increased. In this paper, we propose a novel probabilistic model to analyze reliability of PLC systems, called run-time reliability model (RRM). RRM is automatically constructed based on the structure and run-time execution of the embedded ladder program. Moreover, it is also a dynamic bayesian network (DBN) capturing full dependencies in a PLC system. Then, according to execution semantics of RRM nodes, we present customized conditional probability distribution (CPD) tables to calculate final reliability of the system, with failure probability of every referenced component as refinement. The strength of this model is that not only does it explicitly specify the correlations between run-time execution of embedded software and system components, but also it serves as a computational mechanism for probabilistic inference. Besides, the proposed approach is superior to previous works in both accuracy and efficiency. Compared to monte carlo based simulation, the average error rate of reliability values inferred from RRM model is small.

A Three-State Space Modeling Method for Aircraft System Reliability Design

Reliability is an inherent attribute of a system through optimal system design. However, during the aircraft system development process, the reliability evaluation and system function design efforts are often disconnected, leading to a divide between reliability experts and system designers in their work schedule. This disconnect results in an inefficient aircraft system reliability optimization process, known as the “two-skin” phenomenon. To address this issue, a three-state space model is proposed. Firstly, an analysis was conducted on the relationship between the system function architecture developed by the system designers and the reliability evaluation performed by the reliability experts. Secondly, based on the principle of function flow, the state of failure was categorized into “physical failure” and “non-physical failure”. Additionally, a new state of “function loss” was introduced as the third state for the system, in addition to the traditional states of “normal” and “faulty”. Thirdly, through the state of “Function loss”, an effective integration of system fault modes and function modes was achieved, leading to an optimized system reliability model. A three-state space modeling method was then developed by transforming the system function architecture into a system reliability model. Finally, this new model was applied to an aircraft’s rudder and fly-by-wire control system. The results demonstrate that the function architecture at the design stage of the system can be accurately transformed into the new three-state space model. The structure aligns closely with the function architecture and can be effectively utilized in quantitative system reliability calculations. In this way, the process of ensuring system reliability can be seamlessly integrated into the system optimization design process. This integration alleviates the issue of disjointed work between reliability experts and system designers, leading to a more streamlined and efficient aircraft system optimization process.

Human Error and Clinical Data Sharing

Computer security issues have a widespread impact across all sectors and are increasingly influencing the healthcare industry. Since 2019, several reported attacks have been specifically aimed at exploiting vulnerabilities in medical network protocols like 'DICOM' and 'HL7,' as well as file formats, particularly those related to digital imaging and medical communications. While numerous articles delve into subjects such as security and blockchain, they often disregard the significant role that human errors play in compromising security. Human errors within hospital computer systems can lead to substantial implications for both patient care and data security. This article delves into the various forms of human errors that can occur within such systems and assesses their potential consequences on the overall effectiveness and security of healthcare information management. The study underscores the necessity of effective mitigation strategies to reduce the associated risks of these errors and enhance the dependability of hospital computer systems

MC-reduction simulation approach with heuristic rules for reliability estimation in a multi-state flow network

The system reliability of a multistate flow network (MSFN) holds significant importance as a critical indicator for assessing the probability of successfully transmitting a given demand. It is recognized that evaluating the system reliability of an MSFN presents a challenge due to its NP-hard property. Hence, the paper introduces a novel simulation approach based on minimal cuts (MCs) to estimate the system reliability of an MSFN. The MC-based simulation approach not only enhances computational efficiency during the simulation but also introduces two heuristic rules to remove the MCs that are likely to satisfy the demand. The first rule revolves around the concept of cut size, aiming to reduce the number of the MCs. Subsequently, a saturation threshold is implemented to preserve saturated MCs. By incorporating these two rules, the need to consider all MCs is circumvented, leading to notable gains in computational efficiency during the simulation. Furthermore, the proposed simulation approach effectively deals with non-integer demands directly for the system reliability estimation. Illustrative examples demonstrate the effectiveness and efficiency of the proposed MC-reduction simulation approach. Overall, the reduction in the number of MCs directly translates into a reduction in the time required, underlining the practical benefits of this innovative approach.

A blockchain integration to support failures prediction from log files in multi-agent systems technology

Computer system failures can cause significant financial and reputational damage, making it critical to detect and prevent them before they occur. In this article, we propose a novel approach for predicting system failures based on log file analysis, called MABFailPred. Our approach leverages a Blockchain-based Multi-Agent architecture to analyze execution traces and detect early warning signals for system failure prediction during execution. Moreover, we introduce a new method for extracting log keys called HCLPars. The MABFailPred approach comprises four agents that work together to gather log keys, categorize data, develop a failure model, and make predictions. The use of blockchain ensures that agent and administrator predictions are synchronized, and agent collaboration is coordinated. We validate our approach by applying it to a real-world distributed system and accurately predicting problems before they occur. Our proposed approach represents a significant advancement in the field of system failure prediction, with the potential to enhance the reliability and security of computer systems. By employing a machine learning algorithm, our approach can predict anomalies in real-time and places a strong emphasis on the continuous monitoring of system behavior. The paper includes a validation of the approach using the Hadoop Distributed File System (HDFS) log dataset. According to our findings, the proposed approach achieves superior performance compared to other methods on the same dataset, with a precision of 0.998. This result establishes a new state-of-the-art performance level for the dataset.

A novel reliability redundancy allocation problem formulation for complex systems

Reliability Redundancy Allocation Problem (RRAP) aims to optimize system design with respect to certain resource constraints. For the most of RRAP studies, it is commonly assumed that the subsystems form a series-parallel or bridge structure, while the redundant components in the same subsystem are placed in parallel. To generalize system structures, this paper proposes a novel RRAP for complex systems. The complex system structure is modeled with a graph, where the vertices and edges represent the components and connections between them, respectively. To calculate the system reliability from its structure graph, an automated calculation method based on functionality multi-graph is put forward. The components are classified into various clusters based on the system functionalities they provide, then a multi-graph is constructed by fusing the vertices in the same cluster into a hyper-vertex. Spanning trees are derived from functionality multi-graph, and a validity test is performed to identify valid system configurations. On this basis, a factoring theorem-based algorithm is devised to calculate system reliability. Comparative experiments are carried out on six benchmark problems, the results of which compare favorably to previous RRAP studies. A case study of security system design is also conducted to demonstrate the practicality of our proposed method.

Probabilistic modeling of hardware and software interactions for system reliability assessment

An important aspect of complex hardware-software systems reliability is the interaction between hardware and software. Most of the existing work has assumed either independence between hardware (HW) and software (SW) or a fixed proportion of hardware reported failures to represent HW/SW interactions. These assumptions do not necessarily reflect reality. In this paper, probabilistic HW/SW interactions, in conjunction with hardware and software reliability, are considered to model and assessment overall hardware-software systems reliability. However, incorporating uncertainty demands the use of stochastic programming to estimate the parameters of the hardware reliability model. To capture the HW/SW interactions, a Markov Stochastic process model with uncertainty in transition rates is proposed and solved using Monte Carlo sampling. By combining hardware, software, and probabilistic HW/SW interactions, the overall system reliability can be predicted not only as a point estimator but as quantiles or confidence intervals. The proposed methodology was demonstrated with data from a real computer system provided by Los Alamos National Laboratory. Reliability predictions for a 1,095-day horizon were carried out with an R script in approximately 1.5 s running on a laptop, which demonstrates the feasibility and convenience of the approach. In the four cases analyzed, the 97.5% lower bound of system reliability estimation was above the reliability calculated assuming independent hardware and software reliability.

Reliability Analysis on electric propulsion System Combining GO-FLOW Methodology with Multi-Valued Decision Diagrams

The electric propulsion system of an electric aircraft is the core power of the whole aircraft, which provides assurance for the safe flight of the aircraft. There are multiple stages in the flight process of electric aircraft, as well as different failure behaviors of system components at different stages. The electric motor system is a k-out-of-n system. Therefore, it is not possible to accurately describe the electric motor system with the existing operators when using the GO-FLOW method for electric propulsion system reliability calculations. In order to solve this problem, this paper models the electric motor system using the multi-valued decision diagram method (MDD method), based on which a new operator 43 is proposed to simulate the electric motor system, and then builds the GO-FLOW model and calculates the overall reliability based on the distributed electric propulsion system schematic. The example results show that the method can calculate the reliability of the distributed electric propulsion system more realistically.

Algorithm for Determining the Optimal Weights for the Akushsky Core Function with an Approximate Rank

In this paper, a study is carried out related to improving the reliability and fault tolerance of Fog Computing systems. This work is a continuation of previous studies. In the past, we have developed a method of fast operation for determining the sign of a number in the Residue Number System based on the Akushsky Core Function. We managed to increase the efficiency of calculations by using the approximate rank of a number. However, this result is not final. In this paper, we consider in detail the methods and techniques of the Akushsky Core Function. During research, it was found that the so-called weights can be equal to random variables. Based on the data obtained, we have developed a method for determining the optimal weights for the Akushsky Core Function. The result obtained allows you to obtain a performance advantage due to the preliminary identification of optimal weights for each set of moduli.

Component selection for optimal reliability of a repairable load-sharing system

This study determines the number of components in each subsystem that maximizes the reliability of a load-sharing [Formula: see text] out of [Formula: see text] system when repair is performed at the subsystem level. Previous studies have obtained the system availability given that repair is performed for each component failure. We explain how the statistical flowgraph model is used for computing system reliability under the assumption of an inverse Gaussian distribution for the repair of each subsystem and an exponential distribution for the lifetime of a component operating at a fixed load. A closed-form expression is derived for the transition probability between the system states and the moment generating function of the corresponding waiting time distribution conditional on the transition. By comparing the reliability of systems using different numbers of components in subsystems, we explain how the optimal solution is affected by the repair process and the component homogeneity among subsystems. We discover that, if repair is not considered, it is optimal to use a single subsystem that has the maximum reliability across different operating loads, whereas the use of multiple subsystems is beneficial if repair is performed for a subsystem with a small number of components.

Programmable Molecular Signal Transmission Architecture and Reactant Regeneration Strategy Driven by EXO λ for DNA Circuits.

The characteristics of DNA hybridization enable molecular computing through strand displacement reactions, facilitating the construction of complex DNA circuits, which is an important way to realize information interaction and processing at a molecular level. However, signal attenuation in the cascade and shunt process hinders the reliability of the calculation results and further expansion of the DNA circuit scale. Here, we demonstrate a novel programmable exonuclease-assisted signal transmission architecture, where DNA strand with toehold employed to inhibit the hydrolysis process of EXO λ is applied in DNA circuits. We construct a series circuit with variable resistance and a parallel circuit with constant current source, ensuring excellent orthogonal properties between input and output sequences while maintaining low leakage (<5%) during the reaction. Additionally, a simple and flexible exonuclease-driven reactant regeneration (EDRR) strategy is proposed and applied to construct parallel circuits with constant voltage sources that could amplify the output signal without extra DNA fuel strands or energy. Furthermore, we demonstrate the effectiveness of the EDRR strategy in reducing signal attenuation during cascade and shunt processes by constructing a four-node DNA circuit. These findings offer a new approach to enhance the reliability of molecular computing systems and expand the scale of DNA circuits in the future.