Reliability-Based Software Rejuvenation Scheduling for Cloud-Based Systems

The article analyzes the current stage of educational studies of the cloud-based learning systems. The relationship between the notions of the cloud-based learning system and the cloud-based learning environment are investigated. It was found that the researchers paid most attention to the design of a cloud-based learning environment. However, in the process of a cloud-based environment design, the researchers consider a cloud-based system as a component within the cloud-based learning environment of as a stage in the process of design. It is shown that in the research literature there is no single interpretation of the concept of a cloud-based system for educational purposes. Still the number of basic approaches to the interpretation of the concept under investigation are revealed. The first approach is based on the understanding of the system, as a set of cloud services or cloud-based technologies. The second approach is to consider a separate cloud service as a cloud-based learning system. In this case, the cloud service tools should include such components that cover the content, the tools, the forms and the methods of learning. The structure of the cloud-based learning system within the interpretation of the latest works of Ukrainian researchers is considered.

As businesses increasingly rely on IT for their mission-critical operations, continuous availability is a universal concern. Nowadays, virtualized platform has become the popular option to deploy complex enough services. Deployed services are expected to be always, available, but these long running services are especially sensitive to suffer from software aging phenomenon. Software aging of virtual machine monitors (VMMs) is becoming critical because performance degradation or crash failure of a VMM affects all virtual machines (VMs) on it. To counteract this issue, we deploy software rejuvenation methodology. To eliminate the service outage during software rejuvenation process, we combine the rejuvenation with live migration technology. Live VM migration enables a running VM on a host serer to move onto the other host server with very small interruption of the execution. Live VM migration depends on VMs placement and efficient resource available is required. The idea behind our paper is two-fold. First, we present the optimization of the resource usage as accepting as many services as in virtualized environment which support of VM live migration. Second, to demonstrate how much it can improve system availability, the stochastic Petri nets model a virtualized server system in case of using time based software rejuvenation for VMM is presented. Finally, we perform the numerical analysis to evaluate the model.

Neural network based approach for time to crash prediction to cope with software aging

Continuously running software systems suffer from performance degradation due to aging phenomena and resource exhaustion that are mainly due to error conditions accumulation or due to exhaustion of system resources such as the physical memory. To counteract such phenomena, a periodic preemptive rollback to prevent software failures in the future, called software rejuvenation, can be applied. During the past 20 years, software rejuvenation has been extensively studied with the aim to design rejuvenation policies that optimize system availability, reliability, and performance, mainly in terms of operational cost. In this paper, we propose to model software systems’ overall performance capacity by assigning a performance capacity level at each of the possible states that it can be in, using a continuous time Markov process. A performance capacity indicator for all possible rejuvenation models incorporating partial, full, or both rejuvenation actions is defined and evaluated in the transient, and the steady state phase and the impact of various rejuvenation policies on it are further examined. Our aim is to distinguish the optimal, in terms of performance, rejuvenation strategy consisting of the type of rejuvenation to be implemented and the rejuvenation interval as well. Multi-objective optimization problems are additionally formulated for deriving the rejuvenation policies that optimize the system’s overall performance capacity with respect to availability and operational cost constraints. Numerical examples, in which through comparisons among the rejuvenation models and policies we can distinguish the optimal rejuvenation strategy to be followed, are also presented.

Software aging often affects the performance of a software system and eventually causes it to fail. A novel approach to handle transient software failures is called software rejuvenation which can be regarded as a preventive and proactive solution that is particularly useful for counteracting the phenomenon of software aging. In this paper, we consider the optimal software rejuvenation policy maximizing the interval reliability in the general semi-Markov framework. We derive analytically the optimal software rejuvenation timing which maximizes the limiting interval reliability or the interval reliability with exponentially distributed operation times. Further, we examine numerically the transient behavior of the interval reliability at an arbitrary operation time. Our results under the interval reliability criteria are extentions of some earlier work, since the interval reliability can be specialized to the pointwise availability and the common reliability function.

Software aging often affects the performance of a software system and eventually causes it to fail. To highlight the aging problems in long running applications, we have conducted the study of software rejuvenation approach and virtualization technology in this paper. In order to reduce the downtime during rejuvenation interval, software rejuvenation and virtualization technology are combined in this paper. Virtualization allows multiple operating system instances to run concurrently on a single physical machine. In this paper, we map virtualization based software rejuvenation approach with Markov Chain process and get mathematical steady-state solutions of the chain. We model multiple physical servers which are used to host multiple virtual machines (VMs) using stochastic modeling and evaluate it through both numerical analysis and SHARPE (Symbolic Hierarchical Automated Reliability and Performance Evaluator) tool simulation. The numerical results show that software rejuvenation and virtualization can be used to prolong the availability of the services and reduce the downtime of the systems.

Long running software systems are known to experience an aging phenomenon called software aging, one in which the accumulation of errors during the execution of software leads to performance degradation and eventually results in failure. To counteract this phenomenon a proactive fault management approach, called software rejuvenation, is particularly useful. It essentially involves gracefully terminating an application or a system and restarting it in a clean internal state. In this paper, we evaluate dependability performance of a communication network system with the software rejuvenation under the assumption that the requests arrive according to a Markov modulated Poisson process (MMPP). Three dependability measures, steady-state availability, loss probability of requests and mean response time on tasks, are derived through the hidden Markovian analysis based on the time-based software rejuvenation scheme. In numerical examples, we investigate the sensitivity of some model parameters to the dependability measures.

Software aging affects the availability of Virtual Machine Monitor (VMM), one of the main components of virtualized environments. Software aging causes internal software degradation due to bugs activation and accumulation during its execution. Software rejuvenation implemented through Virtual Machine (VM) Live Migration may be applied to cope with software aging effects on cloud computing system. Another relevant problem is the power consumption of using software rejuvenation techniques in the virtualized environments. This paper presents availability models based on Stochastic Petri Nets to evaluate two VM Live Migration approaches. These approaches are based on the redundancy schemes: Warm-Standby and Cold-Standby. In the Cold-Standby migration, the migration target machine is started only before the VM Live Migration. In the Warm-Standby Migration, the migration target machine runs along with the source migration machine. Results show that VM Live Migration causes a significant improvement in system availability. Scenarios with a heavy workload present an annual downtime reduction of 164 h. The availability comparison between two approaches reveals that the Cold-Standby approach has a slightly better result due to the decrease in the total number of VM Live Migrations. The power consumption results show that Cold-Standby approach is more efficient in power consumption. In all the observed scenarios, the costs savings by using Cold-Standby approach exceed 40%. The highlights of this paper are: i) a comprehensive model for availability evaluation of cloud computing with VMM rejuvenation through VM migration scheduling; ii) sensitivity analysis to define proper rejuvenation scheduling to maximize system availability and iii) power consumption comparison of the two adopted migration approaches.

The current global water crisis, caused by factors such as population growth, urbanization, and climate change, has a significant impact on agriculture, which consumes 70% of the world's freshwater. One potential solution to this problem is the use of intelligent irrigation systems. Cloud-based smart irrigation systems offer a more efficient and cost-effective approach to water consumption management. This study examines the concept of cloud-based smart irrigation systems, their advantages, and their potential application in agriculture. To begin, the authors detail the various components of a cloud-based smart irrigation system, including sensors, controllers, and cloud computing. They then explore the benefits of cloud-based systems, which include scalability, cost-effectiveness, and real-time data processing capabilities. They also delve into the different types of sensors used in smart irrigation systems, such as soil moisture, weather, and crop sensors, as well as their respective advantages and limitations. Furthermore, they discuss the various controllers utilized in smart irrigation systems, such as scheduling, sensor-based, and weather-based controllers. They elaborate on how these controllers function and the advantages they offer in terms of water conservation and crop yield optimization. Lastly, they examine the practical application of cloud-based smart irrigation systems in agriculture, including how to create, implement, and tailor the system to suit the specific requirements of a particular farm. They also consider potential barriers to adoption, such as cost and technological complexity, and how to overcome them. In short, cloud-based smart irrigation systems present a promising solution to the water crisis in agriculture. These systems can significantly reduce water waste, increase crop yield, and save costs by utilizing cloud computing technology to manage irrigation. With careful planning, installation, and configuration, cloud-based smart irrigation systems have the potential to be an effective tool for farmers in improving their productivity and sustainability.

The implementation of cloud-based accounting information systems has significantly transformed modern auditing practices. This study examines the influence of cloud-based system implementation, user understanding level, and data quality on the efficiency of the audit process. This study uses a qualitative approach with case studies on organizations that have implemented cloud-based systems. Data was collected through in-depth interviews, direct observations, and documentation of the audit process. The results show that the implementation of cloud-based systems improves audit efficiency by reducing manual tasks and enabling better data integration. User understanding and high data quality are important factors in ensuring reliable audit results. In addition, organizational readiness and integration with advanced technologies such as big data analytics further strengthen the benefits of cloud-based systems in auditing.

The phenomenon that the state of software degrades with time is known as software aging. The primary method to fight aging is software rejuvenation. This paper presents new ways of effective software rejuvenation using virtualization for addressing software aging. This new approach is meant to be the less disruptive as possible for the running service and to get a zero downtime in most of the cases. We construct the state transition models to describe the behaviors of virtualized and non- virtualized application server. We map through the rejuvenation actions to this transition model with stochastic process and express availability, downtime and downtime costs in terms of the parameters in our models. Our results show that virtualization and software rejuvenation can be used to prolong the availability of the services.

This investigation deals with modeling and availability analysis of cluster-based system inflicted with software aging. Software aging is a phenomenon in which a software system shows performance degradation with time and finally results in software failures. To cope up with this phenomenon, rejuvenation is an innovative concept to recover from software failures. As failures occur, server has the option either to take essential rejuvenation with probability p or may opt for optional rejuvenation with complementary probability q . To achieve high availability of the system, the concept of clustering is also taken into consideration. In this study, restart, reboot and standby concept is used for reducing the downtime cost. The sensitivity analysis of different parameters on system availability has been examined numerically. By integrating clustering, software aging and rejuvenation, the researchers intended to increase the availability and decrease the down time.

Nowadays, several components and systems are designed and produced based on reliability. Since the reliability criterion has an important role in purchasing and implementation of these systems. In the design of a reliable system, fault and failure analysis must be carried out in order to reduce fault probability of the system. When dependency and the relation between components of a complex system are important and should be mentioned, determination of system reliability is very difficult. In this paper, dynamic fault tree is used to evaluate the systems reliability that their behavior is varied with time. Dynamic fault tree is constructed and then it converted to dynamic bayesian network. In this paper, the principle of dynamic fault tree gates and their mapping into dynamic bayesian are explained and some new relations between events and gates for this mapping are proposed. GeNIe package is used to determine dynamic bayesian network based on stochastic sampling algorithms. Four systems (cardiac assist system, hypothetical cascaded priority-and system, inertial navigation system/ global positioning system integrated, and emergency detection system) are investigated; reliability and fault probability of these systems are calculated. Comparison of the results with those obtained by other researches shows the proposed method effectiveness for systems reliability modeling and assessment via dynamic bayesian network.

Software aging refers to performance degradation faced on long-running execution software. The software infrastructure supporting Cloud Computing systems may suffer from aging effects. Such a phenomenon was already reported for virtual infrastructure managers and virtual machine monitors. In this sense, software rejuvenation is a technique of proactive fault tolerance to deal with effects of software aging. This paper proposes a comprehensive availability model for two different types of rejuvenation scheduling based on live migration mechanism, one with a test before migration, and other without. We evaluate five different scenarios, with distinct time intervals for triggering the rejuvenation. The main goal is to explain the benefits gained from the use of this type of rejuvenation technique, as well as understand the differences between the two approaches analyzed. The results show that the utilization of a schedule with a checking mechanism before rejuvenation can bring a significant improvement on system availability.

Society depends increasingly on software based services, necessitating that applications achieve a high level of reliability and availability to maintain customer satisfaction and preserve system safety. These service-oriented applications often operate continuously, which exposes the software to aging where resource deterioration such as memory leaks can lead resource exhaustion and ultimately system failure. To mitigate the impact of aging, software rejuvenation refreshes or restarts the system periodically to recover lost resources, thereby averting failures. Software rejuvenation may also employ fault tolerance to reduce the impact of individual failures on system availability. However, virtually all previous software rejuvenation studies assume that failures experienced by the individual servers comprising a fault tolerant system are statistically independent. This paper analyzes the impact of correlated failures on the optimality of rejuvenation schedules for a system composed of two parallel servers that can experience correlated failures. The examples illustrate the impact of correlation on the optimality of rejuvenation schedules to maximize availability and minimize down time cost. The results indicate that increasing the correlation between the failures of the servers increases the rejuvenation period when the objective is to maximize availability. However, the rejuvenation period decreases when the objective is to minimize down time cost. Thus, the proposed approach can objectively identify the optimal rejuvenation period that maximizes availability or minimizes down time cost.