Vasilis P. Koutras

On the optimization of free resources using non-homogeneous Markov chain software rejuvenation model

Software rejuvenation is an important way to counteract the phenomenon of software aging and system failures. It is a preventive and proactive technique, which consists of periodically restarting an application at a clean internal state. Starting an application generally means that an amount of memory is captured and closing an application engenders the release of an amount of memory. In general, when an application is initiated an amount of memory is captured and when terminated an amount of memory is released. In this paper a model describing the amount of free memory on a system is presented. The modelling is formulated under a continuous time Markov chain framework. Additionally the cost of performing rejuvenation is also taken into consideration, a cost function for the model is produced and a rejuvenation policy is proposed. The contribution of this paper consists of using a cyclic non-homogeneous Markov chain in order to study the overall behaviour of the system capturing time dependence of the rejuvenation rates and deriving an optimal rejuvenation policy. Finally, a case study is presented in order to illustrate the results of the cost analysis.

Semi-Markov Availability Modeling of a Redundant System with Partial and Full Rejuvenation Actions

Software rejuvenation is a preventive maintenance technique to prevent failures in continuously running systems that experience software aging. In this paper, rejuvenation is modeled in a redundant computer system via a semi-Markov process in order to counteract software aging. The system can be switched into the standby unit automatically or manually in the case of a failure at the switching mechanism. Depending on the degradation of the system resources, the running node is either rejuvenated or continues serving and systempsilas steady-state availability is studied along with the optimal time to perform rejuvenation, which increases systempsilas availability. Moreover, an alternative rejuvenation modeling is introduced, in which two different actions; partial and full rejuvenation are performed according to the degradation level. The optimal rejuvenation policies for this case are also derived, leading the system to higher levels of availability.

VoIP Availability and Service Reliability through Software Rejuvenation Policies

Nowadays voice over Internet protocol (VoIP) is becoming an evolutionary technology in telecommunications. In this paper the study is focused on the resources that are allocated for VoIP calls. Resource allocation in a VoIP system and resource degradation when new demands for resources arrive at the system are modeled. To counteract resource degradation and improve availability and service reliability, we propose to perform software rejuvenation.. Moreover, the rate of resource allocation in such a system can be importantly affected by the time that an amount of resources is allocated in order to serve VoIP calls. Hence, we model software rejuvenation in a VoIP system with a semi-Markov process in order to capture the effects of time spent at resource degraded states of the system. Through the stochastic analysis of the system an optimal rejuvenation policy that maximizes systems availability is proposed and furthermore the corresponding reliability levels in means of Mean Time To Failure are derived.

Two-Level Software Rejuvenation Model with Increasing Failure Rate Degradation

Nowadays computer systems fail mainly due to software faults. Consequently the need of improving software availability and reliability arises. One of the main reasons of software failures is software aging. To counteract aging, software rejuvenation has been recently proposed. The main aim when dealing with rejuvenation is to distinguish the optimal time or conditions to trigger it. Rejuvenation can be performed in two levels, partial and full. In this paper, a software system experiencing resource degradation is considered and according to the level of the degradation, partial or full rejuvenation is triggered. Since software performance degrades in time due to the increasing resource exhaustion it is proposed to model the degradation time by an increasing failure rate distribution. The system is modeled by a Semi-Markov process. The purpose is to examine how availability and downtime cost are affected by this fact and moreover to decide on the optimal rejuvenation policy.

Semi-Markov performance modelling of a redundant system with partial, full and failed rejuvenation

Software rejuvenation is a preventive maintenance technique to prevent failures in continuously running systems that experience software aging. In this paper, rejuvenation is modelled in a redundant computer system via a Semi-Markov process in order to counteract software aging. An alternative rejuvenation modelling is also introduced, in which two different actions, partial and full rejuvenation, are performed according to the degradation level. Moreover, the case where software rejuvenation fails to fulfil its purpose leading to a failure is considered. Systems asymptotic availability is studied with respect to the optimal time to perform rejuvenation. Additionally, the expected downtime cost, along with some dependability measures, is also studied. The main purpose of our work is to provide the appropriate framework for finding the optimal rejuvenation interval that will improve not only systems asymptotic availability but also the downtime cost and its performance.

Availability and reliability estimation for a system undergoing minimal, perfect and failed rejuvenation

In this paper, a software rejuvenation model is presented in which two different rejuvenation actions are considered, perfect and minimal. The concept of a failed rejuvenation action which leads the system to failure is also introduced. The presented model is studied under a Continuous Time Markov Chain (CTMC) framework and a maximum likelihood estimator of the generator matrix is presented. Based on this, estimators for instantaneous availability and reliability function are also presented. Moreover, the behavior of the above estimators is studied under various rejuvenation policies. A numerical example based on simulation results is finally presented.

Optimization of the dependability and performance measures of a generic model for multi-state deteriorating systems under maintenance

In this paper, a general model for multi-state deteriorating systems with condition based preventive maintenance is introduced and analyzed extensively. The system experiences various levels of deterioration and at each stage, an inspection is carried out at constant time intervals in order to identify what kind of preventive maintenance, the system should undergo. When the system fails, despite preventive maintenance, a repair procedure is carried out and the system is restored to its initial fully operational state. The proposed model incorporates also imperfect maintenance, either minimal or major, failed maintenance and sudden failures that may occur mostly due to external factors at any deterioration state as well. Moreover, the sojourn times are assumed to be generally distributed. The main dependability and performance measures of the proposed model are computed while the corresponding transient measures are estimated using Monte Carlo simulation. Our endmost aim is to distinguish inspection and consequently maintenance policies that optimize multi-state deteriorating systems dependability and/or performance. Additionally, multi-objective optimization problems are formulated and solve in order to distinguish preventive maintenance policies that optimize simultaneously both the dependability and performance measures.

Optimizing the Availability and the Operational Cost of a Periodically Inspected Multi-state Deteriorating System with Condition Based Maintenance Policies

In this paper a multi-state deterioration system which experiences several states of performance degradation until it fails is studied extensively and condition-based preventive maintenance policies are examined. The optimal maintenance policy aims at maximizing systems asymptotic availability and at minimizing its total operational cost, with respect to the two different inspection intervals. For the simultaneous optimization of the aforementioned measures, multi-objective optimization methods are employed. In the current work, the inspection times are assumed to be constant, thus the systems evolution in time is modeled by a semi-Markov process. Finally, the proposed system is compared with the corresponding Markov one which is the most commonly used approximation of the original system in practice.

Software rejuvenation for resource optimization based on explicit approximate inverse preconditioning

When software applications run continuously, error conditions are accumulated and the result is a degradation of the computer system or even a crash failure. This phenomenon has been reported as software aging. A proactive method in order to counteract this phenomenon is software rejuvenation. In this paper, two software rejuvenation techniques are presented in a computer system in which the amount of free memory is used in order to model the resource degradation of the system. Furthermore, the cost of each technique is determined and the two techniques are compared with respect to the total expected downtime cost of performing rejuvenation and one of them is proposed. In addition, useful results about the rates of performing rejuvenation are derived and finally an optimal rejuvenation policy is proposed for such a computer system.

Applying Partial and Full Rejuvenation in Different Degradation Levels

In this paper, a two-level software rejuvenation model is introduced. The innovative aspect consists in combining partial, full and failed rejuvenation with the concept of triggering rejuvenation even if the software did not reach the failure probable state. In the later case, either partial or full rejuvenation actions can be performed. The aim is to observe the effects of partial and full rejuvenation frequencies on systems performance, in order to distinguish optimal rejuvenation schedules. Systems performance is expressed through availability, downtime and rejuvenation cost indicators.