scholarly journals Availability Modelling of Cluster-Based System with Software Aging and Optional Rejuvenation Policy

2019 ◽  
Vol 19 (4) ◽  
pp. 90-100
Author(s):  
Richa Sharma ◽  
Gireesh Kumar
Keyword(s):  
Sensitivity Analysis ◽  
Performance Degradation ◽  
High Availability ◽  
Software System ◽  
System Availability ◽  
Software Failures ◽  
Software Aging ◽  
Availability Analysis ◽  
Innovative Concept

Abstract 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.

scholarly journals SIP Policy: Theoretical and Conceptual Facts of Software Rejuvenation in Convoluted System

2016 ◽  
Vol 1 (1) ◽  
pp. 35
Author(s):  
Nagaraj G Cholli ◽  
Srinivasan G N
Keyword(s):  
Operating System ◽  
System Performance ◽  
Performance Degradation ◽  
High Availability ◽  
Numerical Error ◽  
Main Issue ◽  
Software Aging ◽  
Software Rejuvenation ◽  
Software Failure ◽  
Novel Approach

A software aging in convoluted system refers to the situation where software degrades with span of time. This phenomenon, which may eventually lead to system performance degradation or crash/hang failure, is the result of depletion of operating system resources, data deception and numerical error assembly. A technique called software rejuvenation has been incorporated, which essentially involves periodic aborting an application or a system, flushing its intramural state and re-starting it. A main issue in rejuvenation is to discover ideal time to initiate software rejuvenation. Software rejuvenation is a proactive technique that allows preventing the occurrence of software failing. A novel approach called Smart interval and payload (SIP) policy is introduced to overcome all the hurdles in the present scenario based on Software Rejuvenation approaches. SIP policy accepts time from user and optimizes the rejuvenation time whenever workload is variable; otherwise the system is rejuvenated at its rejuvenation point. SIP policy avoids software failure and it helps to achieve high availability of convoluted system.

Markovian Availability Measurement and Assessement for Hardware-Software System

1997 ◽  
Vol 04 (03) ◽  
pp. 257-268 ◽  
Author(s):  
Koichi Tokuno ◽  
Shigeru Yamada
Keyword(s):  
System Reliability ◽  
Software Systems ◽  
Software System ◽  
Reliability Growth ◽  
System Availability ◽  
Software Failures ◽  
Software Failure ◽  
Dependent Behavior ◽  
Reliability Performance ◽  
Availability Model

It is important to take into account the trade-off between hardware and software systems when total computer-system reliability/performance are evaluated and assessed. We develop an availability model for a hardware-software system. The system treated here consists of one hardware subsystem and one software subsystem and it is assumed that the system is down and restored whenever a hardware or a software failure occurs. Especially, for the software subsystem, it is supposed that (i) the restoration actions are not always performed perfectly, (ii) the restoration times for later software failures become longer and (iii) reliability growth occurs in the perfect restoration action. The hardware and the software failure-occurrence phenomena are respectively described by constant and geometrically decreasing hazard rates. The time-dependent behavior of the system, which alternately repeats the operational state that a system is operating without failures and the restoration state that a system is inoperable and restored, is described by a Markov process. Useful expressions for several quantitative measures of system performance are derived from this model. Finally, numerical examples are presented for illustration of system availability measurement and assessment.

scholarly journals Degrading systems availability analysis: analytical semi-Markov approach

2021 ◽  
Vol 23 (1) ◽  
pp. 195-208
Author(s):  
Varun Kumar ◽  
Girish Kumar ◽  
Rajesh Kumar Singh ◽  
Umang Soni
Keyword(s):  
Steady State ◽  
Degradation Mechanism ◽  
Continuous Process ◽  
Mechanical Systems ◽  
Embedded Markov Chain ◽  
Steady State Probability ◽  
Opportunistic Maintenance ◽  
System Availability ◽  
Availability Analysis ◽  
Complex Mechanical Systems

This paper deals with modeling and analysis of complex mechanical systems that deteriorate with age. As systems age, the questions on their availability and reliability start to surface. The system is believed to suffer from internal stochastic degradation mechanism that is described as a gradual and continuous process of performance deterioration. Therefore, it becomes difficult for maintenance engineer to model such system. Semi-Markov approach is proposed to analyze the degradation of complex mechanical systems. It involves constructing states corresponding to the system functionality status and constructing kernel matrix between the states. The construction of the transition matrix takes the failure rate and repair rate into account. Once the steady-state probability of the embedded Markov chain is computed, one can compute the steady-state solution and finally, the system availability. System models based on perfect repair without opportunistic and with opportunistic maintenance have been developed and the benefits of opportunistic maintenance are quantified in terms of increased system availability. The proposed methodology is demonstrated for a two-stage reciprocating air compressor with intercooler in between, system in series configuration.

The development of the TRAP-97 software system. A sensitivity analysis

2006 ◽  
Vol 53 (1) ◽  
pp. 53-61 ◽  
Author(s):  
M. A. Bykov ◽  
S. I. Zaitsev ◽  
G. V. Alekhin ◽  
S. A. Kurbaev ◽  
A. P. Egorov ◽  
...  
Keyword(s):  
Sensitivity Analysis ◽  
Software System ◽  
System A

A Local Approach and Comparison with Other Data Mining Approaches in Software Application

2017 ◽  
pp. 1-26
Author(s):  
QingE Wu ◽  
Weidong Yang
Keyword(s):  
Data Mining ◽  
Fault Diagnosis ◽  
Forecast Accuracy ◽  
Software System ◽  
Local Approach ◽  
Test Analysis ◽  
Software Application ◽  
Software Aging ◽  
Optimum Approach ◽  
Sensitivity Specificity

In order to complete an online, real-time and effective aging detection to software, this paper studies a local approach that is also called a fuzzy incomplete and a statistical data mining approaches, and gives their algorithm implementation in the software system fault diagnosis. The application comparison of the two data mining approaches with four classical data mining approaches in software system fault diagnosis is discussed. The performance of each approach is evaluated from the sensitivity, specificity, accuracy rate, error classified rate, missed classified rate, and run-time. An optimum approach is chosen from several approaches to do comparative study. On the data of 1020 samples, the operating results show that the fuzzy incomplete approach has the highest sensitivity, the forecast accuracy that are 96.13% and 94.71%, respectively, which is higher than those of other approaches. It has also the relatively less error classified rate is or so 4.12%, the least missed classified rate is or so 1.18%, and the least runtime is 0.35s, which all are less than those of the other approaches. After the performance, indices are all evaluated and synthesized, the results indicate the performance of the fuzzy incomplete approach is best. Moreover, from the test analysis known, the fuzzy incomplete approach has also some advantages, such as it has the faster detection speed, the lower storage capacity, and does not need any prior information in addition to data processing. These results indicate that the mining approach is more effective and feasible than the old data mining approaches in software aging detection.

MARKOVIAN AVAILABILITY MEASUREMENT WITH TWO TYPES OF SOFTWARE FAILURES DURING THE OPERATION PHASE

1999 ◽  
Vol 06 (01) ◽  
pp. 43-56 ◽  
Author(s):  
KOICHI TOKUNO ◽  
SHIGERU YAMADA
Keyword(s):  
System Performance ◽  
Hazard Rate ◽  
Software System ◽  
Cumulative Number ◽  
Imperfect Debugging ◽  
Software Failures ◽  
Software Failure ◽  
Dependent Behavior ◽  
Operation Phase ◽  
Availability Model

This paper develops a plausible software availability model considering two types of failures during the operation phase. The first type is caused by the faults that could not be detected/corrected during the testing phase and the second type caused by those introduced by deviating from the specification during the operation phase. The former and the latter types of software failure-occurrence phenomena are described by a geometrically decreasing and a constant hazard rate, respectively. This model also describes the imperfect debugging environment in which a debugging activity does not always remove a fault perfectly. Taking notice of the cumulative number of faults corrected during the operation phase, we use a Markov process to describe the time-dependent behavior of the software system. Several quantitative measures of software system performance are derived from this model. Finally, numerical examples are presented for illustration of software availability measurement.

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