scholarly journals Optimization of Two-Granularity Software Rejuvenation Policy Based on the Markov Regenerative Process

2016 ◽  
Vol 65 (4) ◽  
pp. 1630-1646 ◽  
Author(s):  
Gaorong Ning ◽  
Jing Zhao ◽  
Yunlong Lou ◽  
Javier Alonso ◽  
Rivalino Matias ◽  
...  
Keyword(s):  
Regenerative Process ◽  
Software Rejuvenation ◽  
Markov Regenerative Process

ESTIMATING DISCRETE-TIME PERIODIC SOFTWARE REJUVENATION SCHEDULES UNDER COST EFFECTIVENESS CRITERION

2006 ◽  
Vol 13 (06) ◽  
pp. 565-579
Author(s):  
KAZUKI IWAMOTO ◽  
TADASHI DOHI ◽  
NAOTO KAIO
Keyword(s):  
Asymptotic Behavior ◽  
Cost Effectiveness ◽  
Discrete Time ◽  
Parametric Method ◽  
Regenerative Process ◽  
Numerical Examples ◽  
Software Aging ◽  
Software Rejuvenation ◽  
Markov Regenerative Process ◽  
Time Periodic

Software rejuvenation is a preventive and proactive solution that is particularly useful for counteracting the phenomenon of software aging. In this article, we consider the similar periodic software rejuvenation model to Garg et al.13 under the different operation circumstance. That is, we model the stochastic behavior of telecommunication billing applications by using a discrete-time Markov regenerative process, and determine the optimal periodic software rejuvenation schedule maximizing the so-called cost effectiveness, in discrete-time setting. Also, we provide a statistically non-parametric method to estimate the optimal software rejuvenation schedule, based on the discrete total time on test concept. Numerical examples are devoted to illustrate the determination/estimation of the optimal software rejuvenation schedule and to examine the asymptotic behavior of the estimator developed here.

Preventive Maintenance of Multi-State System with Phase-Type Failure Time Distribution and Non-Zero Inspection Time

2003 ◽  
Vol 10 (03) ◽  
pp. 323-344 ◽  
Author(s):  
Dongyan Chen ◽  
Yonghuan Cao ◽  
Kishor S. Trivedi ◽  
Yiguang Hong
Keyword(s):  
Preventive Maintenance ◽  
Failure Time ◽  
Regenerative Process ◽  
Inspection Time ◽  
Maintenance Policy ◽  
System Availability ◽  
Failure Time Distribution ◽  
Set Up ◽  
Markov Regenerative Process ◽  
The Mathematical Model

Preventive maintenance is applied to improve the system availability or decrease the operational cost. This paper addresses the optimal preventive maintenance problem for multi-state deteriorating systems, where the system experiences multiple stages of performance degradation before it fails. We consider a general case where the inspection and repair time are generally distributed. The threshold type maintenance policy is employed for preventive minor maintenance and preventive major maintenance, where minor or major maintenance is carried out when the system deterioration stage is found to be larger than certain thresholds. The mathematical model of the system is set up by means of a Markov regenerative process (MRGP). With this formulation, the system steady-state probabilities under consideration are computed.

scholarly journals A Markov regenerative process with recurrence time and its application

2021 ◽  
Vol 7 (1) ◽  
Author(s):  
Puneet Pasricha ◽  
Dharmaraja Selvamuthu
Keyword(s):  
Credit Rating ◽  
Transition Probabilities ◽  
Statistical Tests ◽  
Regenerative Process ◽  
Recurrence Time ◽  
Recurrence Times ◽  
Proposed Model ◽  
Special Cases ◽  
Markov Regenerative Process ◽  
Semi Markov Processes

AbstractThis study proposes a non-homogeneous continuous-time Markov regenerative process with recurrence times, in particular, forward and backward recurrence processes. We obtain the transient solution of the process in the form of a generalized Markov renewal equation. A distinguishing feature is that Markov and semi-Markov processes result as special cases of the proposed model. To model the credit rating dynamics to demonstrate its applicability, we apply the proposed stochastic process to Standard and Poor’s rating agency’s data. Further, statistical tests confirm that the proposed model captures the rating dynamics better than the existing models, and the inclusion of recurrence times significantly impacts the transition probabilities.

scholarly journals Availability Analysis of Software Systems with Rejuvenation and Checkpointing

Mathematics ◽  
2021 ◽  
Vol 9 (8) ◽  
pp. 846
Author(s):  
Junjun Zheng ◽  
Hiroyuki Okamura ◽  
Tadashi Dohi
Keyword(s):  
Steady State ◽  
Human Error ◽  
System Modeling ◽  
Regenerative Process ◽  
State System ◽  
Software Systems ◽  
System Availability ◽  
Software Rejuvenation ◽  
Availability Analysis ◽  
Availability Model

In software reliability engineering, software-rejuvenation and -checkpointing techniques are widely used for enhancing system reliability and strengthening data protection. In this paper, a stochastic framework composed of a composite stochastic Petri reward net and its resulting non-Markovian availability model is presented to capture the dynamic behavior of an operational software system in which time-based software rejuvenation and checkpointing are both aperiodically conducted. In particular, apart from the software-aging problem that may cause the system to fail, human-error factors (i.e., a system operator’s misoperations) during checkpointing are also considered. To solve the stationary solution of the non-Markovian availability model, which is derived on the basis of the reachability graph of stochastic Petri reward nets and is actually not one of the trivial stochastic models such as the semi-Markov process and the Markov regenerative process, the phase-expansion approach is considered. In numerical experiments, we illustrate steady-state system availability and find optimal software-rejuvenation policies that maximize steady-state system availability. The effects of human-error factors on both steady-state system availability and the optimal software-rejuvenation trigger timing are also evaluated. Numerical results showed that human errors during checkpointing both decreased system availability and brought a significant effect on the optimal rejuvenation-trigger timing, so that it should not be overlooked during system modeling.

Quantifying Resiliency of Virtualized System with Software Rejuvenation

2015 ◽  
Vol E98.A (10) ◽  
pp. 2051-2059 ◽  
Author(s):  
Hiroyuki OKAMURA ◽  
Jungang GUAN ◽  
Chao LUO ◽  
Tadashi DOHI
Keyword(s):  
Software Rejuvenation

Design of distributed and self-adaptive performance monitoring system based on software rejuvenation

2010 ◽  
Vol 30 (6) ◽  
pp. 1642-1644
Author(s):  
Jing YOU ◽  
Kang-ning XU ◽  
Hong-yuan WANG ◽  
Ya-nan YANG ◽  
Jin-shu GAO
Keyword(s):  
Monitoring System ◽  
Performance Monitoring ◽  
Adaptive Performance ◽  
Software Rejuvenation ◽  
Self Adaptive

scholarly journals Software Rejuvenation Under Persistent Attacks in Constrained Environments

2020 ◽  
Vol 53 (2) ◽  
pp. 4088-4094
Author(s):  
Raffaele Romagnoli ◽  
Paul Griffioen ◽  
Bruce H. Krogh ◽  
Bruno Sinopoli
Keyword(s):  
Software Rejuvenation ◽  
Constrained Environments
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