Warm Standby Research Articles

System reliability analysis of retrial machine repair systems with warm standbys and a single server of working breakdown and recovery policy

AbstractReliability analysis plays an important role in the machine repair systems. The purpose of this study is to propose reliability analysis of retrial machine repair systems with M operating units, W warm standby units, and a single repair server with recovery policy. Failure times, repair times, and retrial times for all units are assumed to follow exponential distributions. The single repair server is subject to breakdown, and failure times and repair times for the single server are also assumed to follow exponential distributions. The recovery policy is considered in this study to efficiently utilize the single repair server. Based on the transition rate diagram, the probability differential equations are derived, and Laplace transforms are then taken on these equations to derive system reliability and the mean time to system failure (MTTF). Both sensitivity analyses and relative sensitivity analyses are also performed. Some numerical experiments are designed and executed. The important results are outlined below. The failure rate of an operating unit (λ) significantly influences system reliability. Threshold of the recovery policy (q), the service rate of the working server (μ1), and the breakdown rate of the server (α) affect system reliability moderately. The service rate of the broken down server (μ2), the retrial rate (θ), and the repair rate to repair the broken down server (β) affect system reliability slightly; the failure rate of a standby unit (η) rarely influences system reliability. Furthermore, λ affects MTTF significantly, influence MTTF moderately, slightly affect MTTF, and η rarely affects MTTF.

Cost analysis of systems with mixed standby units

This paper deals with evaluation of cost of four dissimilar configurations with mixed standby units. The standby units exist as warm and cold standby. It is assumed that failure and repair time of all units are assumed to be exponentially distributed. Explicit expressions for busy period of repairmen, steady-state availability and profit function are derived using linear first order differential equations. Several cases are analysed graphically to investigate the effects of various system parameters on profit. The paper also presents graphical comparison for specific values of system parameters and finds that the optimal system configuration is configuration I.

N-policy for redundant repairable system with multiple types of warm standbys with switching failure and vacation

N-policy for redundant repairable system with multiple types of warm standbys with switching failure and vacation

N-policy for redundant repairable system with multiple types of warm standbys with switching failure and vacation

This investigation is concerned with the reliability analysis of redundant repairable system which is supported by mixed standby and two repairmen who turn on according to a threshold N-policy. The first repairman never takes a vacation while the second repairman leaves for a vacation of random length when the number of failed components is less than N. The concepts of standby switching failure, degradation and common cause failure are incorporated to predict the performance metrics of the real time redundant repairable system. By developing Markov model, the transient queue size distribution and expressions for the system reliability, mean time to system failure and other performance measures are obtained. The sensitivity analysis is performed by taking numerical illustration. The model is also examined computationally by employing the adaptive network-based fuzzy interference system (ANFIS) approach to compute the system descriptors. Using supervised learning process, the comparison between the ANFIS results and analytical results are made.

The backup recovery strategy selection to maintain the business continuity plan

Indonesia faces the risks of volcanic eruptions, earthquakes, floods and tsunamis, which destruct its land areas and also result in damage to client and server computer systems. The demand for the information technology availability and performance becomes high. Disaster recovery plan is designed to ensure the vital business processes continuation in the event a disaster occurs. The problem is how to make the best way in selecting backup recovery strategy based on the benefits to the cost ratio so as to minimize the business losses that will be caused by the failure of an application system. This research aims to make decisions that can help make certain parties take the best decision in choosing the backup recovery strategy for a business continuity plan in the Trilogy University. The research method used is the multi-criteria decision-making and analytical hierarchy process by using the expert choice software. From the research results can be concluded that the first order in backup strategy is hot standby option 59,4%, followed by cold standby option 23,3%, then the choice of warm standby option 17,4%. The data inconsistency rate is 0.02, smaller than 0.1 as the maximum value of inconsistency ratio.

Cost benefit analysis of three systems with imperfect coverage and standby switching failures

The cloud computing is an emerging new computing paradigm which provides high reliability, high availability, and QoS-guaranteed computing services. The reliability and stability of power supply is one of the most important factors in successful cloud computing. In this paper, we compare three different configurations with imperfect coverage and standby switching failures based on system reliability and availability. The time-to-repair and the time-to-failure for each of the primary and warm standby components are assumed to be exponentially distributed. We derive the explicit expressions for mean time-to-failure, MTTF, and steady-state availability, AT(∞), for three configurations and perform a comparative analysis. Three configurations are ranked based on MTTF, AT(∞), and cost/benefit where benefit is either MTTF or AT(∞).

Co-optimization of state dependent loading and mission abort policy in heterogeneous warm standby systems

This paper models and optimizes a 1-out-of-N: G heterogeneous warm standby system subject to state-dependent component loading and mission abort policies. For circumstances where a system's survival may have a higher priority than continuing a specified mission due to cost or safety reasons, when a certain incident or malfunction condition is met based on a predefined decision rule, the mission objective is aborted and a rescue procedure is performed for system survival. The mission abort policy implemented can affect the system performance significantly. In addition, load levels of system components affect their performances (e.g., productivity) and time-to-failure distributions, and further affect the overall system performance. This paper makes new contributions by formulating and solving a co-optimization problem that finds the optimal combination of mission abort and component loading policies, maximizing the mission success probability while providing a desired level of system survivability. As demonstrated through examples, the co-optimization results can facilitate optimal decisions on effective and safe operations management of warm standby systems.

Availability Modeling of Generalized $k$ -Out-of- $n$ :G Warm Standby Systems With PEPA

Developing analytical availability models for ${k}$ -out-of- ${n}$ :G warm standby repairable systems with many nonidentical components is tedious and error-prone, requiring specification of the generator matrix of a high dimensional Markov chain. Using the performance evaluation process algebra (PEPA) as an intermediary, this paper gives a new modeling approach for availability evaluation of such systems with ${r}$ repair facilities. The components of the system are classified into ${n}$ different groups that consist of statistically identical components following exponential time-to-failure and repair time distributions. A library of PEPA components and their actions are defined for system component groups, repair facilities, repair queue, and system dynamics. To capture the dependency of system states on components, a signaling mechanism is realized by actions with suitably high rates. A compilation tool is provided to automatically generate the PEPA model from a brief specification of the system, using the library components. This provides input for the PEPA analysis tool and is amenable to availability analysis. Examples are used to illustrate the proposed modeling method. Modeling with PEPA provides an efficient way to deal with availability evaluation of systems considered with many groups of repairable components.

Optimization of Component Allocation/Distribution and Sequencing in Warm Standby Series-Parallel Systems

Existing works on redundancy allocation problems have typically focused on active or cold standby redundancies or a mix of them; little research is dedicated to warm standby systems but with an assumption of allocating the same choice of components within each subsystem. Motivated by the fact that components with different costs and failure time distributions from different vendors can be available for the design of the same subsystem in practice, this paper advances the state-of-the-art by presenting a solution methodology to determine combined optimal design configuration and optimal operation of heterogeneous warm standby series-parallel systems. Particularly, based on a proposed numerical reliability evaluation algorithm, two combined optimization problems (component allocation and sequencing problem, and component distribution and sequencing problem) are formulated and solved. Necessity and significance of the proposed methodology are illustrated through examples. Efficiency of the methodology is also successfully demonstrated on large warm standby series-parallel systems containing 14 subsystems of different choices of components.

Heterogeneous standby systems with shocks-driven preventive replacements

The paper considers heterogeneous 1-out-of-N warm standby systems when all components can experience internal failures and operating components are exposed to external shocks. The components’ resilience to shocks decreases with the number of experienced shocks. A preventive replacement policy when the operating component is replaced after it survives a certain number of shocks is considered. A numerical algorithm for evaluating the expected mission costs and the mission success probability is suggested. An optimization problem for a replacement policy that minimizes the expected mission cost providing a desired level of a mission success probability is formulated and solved. Illustrative examples are provided.

Optimizing availability of heterogeneous standby systems exposed to shocks

The paper considers heterogeneous 1-out-of-N warm standby systems when all components can experience internal failures whereas operating components are exposed to the external shocks as well. The components’ resilience to shocks decreases with the number of experienced shocks describing the corresponding deterioration in time. Therefore, a preventive replacement policy when the operating component is replaced after it survives a certain number of shocks (that becomes a decision parameter) is considered. The replacement time is random and not negligible. The distributions of corrective and preventive replacement times are assumed to be known for each component. The expression for the instantaneous (point) availability is derived and the original numerical algorithm for its evaluation is suggested. Then an optimization problem for a replacement policy that maximizes the overall mission availability over a finite time horizon is formulated and solved. Illustrative examples are provided.

An availability-based system with general repair via Bayesian aspect

We study the Bayesian inferences of an availability system with reboot delay and standby switching failures, in which the system consists of one active component and one warm standby. The system is studied under the assumption that the time-to-failure and the time-to-repair are assumed to follow an exponential and a general distribution. The reboot time is assumed to be exponentially distributed with parameter β. There is always the failure possibility c during the switching process from standby-component state to the active-component state. To implement the simulation inference for the system availability, two repair-time distributions, namely, the lognormal and Erlang distributions characterized by their shape parameters are considered. Finally, all simulation results are displayed by appropriate tables and curves to analyze the performance of the statistical inference procedures.

Reliability Evaluation for Demand-Based Warm Standby Systems Considering Degradation Process

Warm standby redundancy is a fault-tolerant technique balancing the low economical efficiency of hot standby and the long recovery time of cold standby. In this paper, motivated by practical engineering systems, a general demand-based warm standby system (DB-WSS) considering component degradation process is studied. A series of intermediate states exists between perfect functionality and complete failure because of degradation processes. A lot of existing analytical reliability assessment techniques are focused on conventional binary-state models or exponential state transition distributions for a system or its components. In this paper, a novel reliability evaluation approach based on the multistate decision diagram for DB-WSS is proposed. The proposed technique can handle arbitrary distributions of degradation processes for multistate components or systems. Moreover, considering the imperfect switch of the warm standby component, the start failure probability is taken into account in the warm standby system. Numerical studies are given to illustrate the proposed approach.

Preventive Replacements in Real-Time Standby Systems With Periodic Backups

This paper models a real-time warm standby system that has to accomplish a specified amount of task by a hard deadline. The system is subject to corrective replacements (CRs) upon failure of its operating element. It can also be renewed according to a predetermined schedule through preventive replacements (PRs). To facilitate an effective recovery of system operation after replacements, periodic backups are performed so that warm standby elements, upon being activated, can take over the mission task from the last backup point instead of from scratch. This paper presents a novel integrated model that considers effects of periodic backups, CRs and PRs in analyzing and optimizing real-time warm standby systems. Mission success probability and expected mission completion time are evaluated. Impacts of different mission and element parameters on mission success probability, optimal backup and PR policies, and optimal element activation sequence are investigated. It is shown that in warm standby systems with periodic backups and tight deadlines, PRs can improve the mission success probability even when they take the same time as CRs. When the maximum allowed mission time exceeds a certain level, PRs become ineffective and the optimal policy can involve only periodic backups.

Heterogeneous 1-out-of-N warm standby systems with online checkpointing

As a common practice in computing-related applications, checkpointing is used to facilitate an effective system recovery in the case of the occurrence of failures. Checkpoints are performed to save data associated with completed portion of a mission task. In the case of a failure, through rollback and data retrieval the system can resume the mission task from the last successful checkpoint instead of from the very beginning of the mission, saving time and cost. This paper models and optimizes 1-out-of-N: G warm standby systems subject to uneven online checkpointing, where checkpoints can be performed in parallel with execution of the primary mission task for improving efficiency of computing elements. Both data checkpoint and retrieval take dynamic time, depending on the amount of work completed. System elements can be heterogeneous in the time-to-failure distribution, performance, and level of readiness to take over the mission task during the warm standby mode. A numerical method is first suggested to evaluate mission performance indices including mission success probability, expected mission completion time, and expected mission operation cost. Examples are provided to demonstrate influence of mission deadline and element resource sharing parameter (i.e., CPU time distribution between the checkpointing procedure and the primary mission task) on the mission performance metrics. The optimal checkpoint distribution and optimal element activation sequencing problems are considered for different combinations of optimization objectives and constraints. A co-optimization problem is further addressed, which aims to find the optimal combination of checkpoint distribution and element activation sequence. Example optimization solutions illustrate the tradeoff among the three mission requirements (reliability, completion time, operation cost) for warm standby systems with online checkpoints.

Estimation of stress-strength reliability of a parallel system with active, warm and cold standby components

In this paper we estimate the stress–strength reliability of a parallel system with l active components, s warm standby components, and k cold standby components. We assume perfect switching among the components from warm standby mode to active mode and from cold standby mode to warm standby mode. A reduced stress for the warm standby components is introduced and the components may fail in the warm standby mode. The reliability of the parallel system is evaluated by assuming the stress and strength of the components to be independent random variables. We derive the expression of reliability of the system by assuming both the stress and strength of the components having Exponential, Weibull, and Lomax distributions, respectively. The method of maximum likelihood estimation is used to obtain the reliability estimators. Illustrations are provided through an example using MATLAB programming.

Generalized control-limit preventive repair policies for deteriorating cold and warm standby Markovian systems

ABSTRACTConsider a deteriorating repairable Markovian system with N stochastically independent identical units. The lifetime of each unit follows a discrete phase-type distribution. There is one online unit and the others are in standby status. In addition, there is a single repair facility and the repair time of a failed unit has a geometric distribution. The system is inspected at equally spaced points in time. After each inspection, either repair or a full replacement is possible. We consider state-dependent operating costs, repair costs that are dependent on the extent of the repair, and failure penalty costs. Applying dynamic programming, we show that under reasonable conditions on the system’s law of evolution and on the state-dependent costs, a generalized control-limit policy is optimal for the expected total discounted criterion for both cold standby and warm standby systems. Illustrative numerical examples are presented and insights are provided.

Optimal arrangement of connecting elements in linear consecutively connected systems with heterogeneous warm standby groups

Motivated by practical applications such as radio communication and flow transmission systems, this paper models and optimizes linear consecutively connected systems (LCCS) with a set of linearly ordered nodes. Each node may contain multiple connection elements (CE) configured as a warm standby structure, where one CE is online providing a connection between its host node and a certain number of next nodes along the sequence, with the remaining CEs serving as standbys. CEs have heterogeneous types characterized by different time-to-failure distributions and connection ranges. An iterative algorithm is first proposed for determining performance stochastic processes of particular CE standby groups. A universal generating function technique is then used for evaluating instantaneous and expected system connectivity for the considered LCCS. An optimization problem of CE distribution and sequencing is further defined and solved, with the objective of finding CE distribution among LCCS nodes and sequencing of CE activation in standby groups to maximize the expected system connectivity over a specified mission time horizon. Optimization results are useful in guiding optimal decisions on reliable design and operation of LCCSs. Examples are provided to demonstrate application of the proposed methodology and optimization problem.

Optimal backup in heterogeneous standby systems exposed to shocks

The paper considers non-repairable 1-out-of-N heterogeneous warm standby computing systems with components exposed to internal failures and external shocks. To provide the data recovery in the case of operating component failure, the backup procedures are performed during the computational mission. The backups enable an activated standby component to take over the mission task from the point where the last backup has been completed without redoing the entire task from scratch. Both data backup and retrieval times depend on the amount of work performed. The system components are characterized by a different performance level, replacement time, time-to-internal failure distribution, and shocks survival probability. The shock processes also have different characteristics for different components. A numerical method is proposed to evaluate mission success probability for a given allowed mission time and expected mission completion time. The optimal backup scheduling problem is then formulated and solved for different optimization objectives and constraints.

Dual-System Warm Standby of Remote Sensing Satellite Control System Technology

Standby is a technique that has been widely applied to improve system reliability and availability in the stage of system design. For satellite control system, it requires features of high reliability, security and sustainability. In this paper, we design a dual-system warm standby technology. The system consists of double control servers, one is operating control server and another one is standby control server. Dual-system warm standby log files use differential ghost method that can’t only strengthen log real-time but also reduce network usage. Erasing log files after the operation is completed that can reduce reliance on storage memory. When switching to backup server, according to the dual-system warm backup log files, it can recover the current mission progress and continue to run the mission. Through experimental verification, the design has a good reliability and stability. It can be widely used in aerospace field test.