Statistical non-parametric algorithms to estimate the optimal software rejuvenation schedule

Dohi, Tadashi; Goševa-Popstojanova, Katerina; Trivedi, Kishor S.

doi:10.1109/prdc.2000.897287

Cited by 81 publications

(44 citation statements)

References 9 publications

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“…This approach is suitable to treat symptoms of aging that happens for technical reasons rather than changes in requirements. Dohi et al [13] models optimal rejuvenation schedule using semi-Markov processes to maximize availability and minimize cost. The focus here is aging caused due to processing attributes; however, unlike this work we focus on the functionality attributes of a system Garg et al [14].…”

Section: Related Workmentioning

confidence: 99%

A Simple Software Rejuvenation Framework Based on Model Driven Development

Mahmud

2017

UHDJST

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A B S T R A C TIn the current dynamic-natured business environment, it is inevitable that today's software systems may not be suitable for tomorrow's business challenges which indicate that the software in use has aged. Although we cannot prevent software aging, we can try to prolong the aging process of software so that it can be used for longer. In this paper, we outline a conceptual software rejuvenation framework based on model driven development approach. The framework is simple but effective and can be implemented in a recursive five step process. We have illustrated the applicability of the framework using a simple business case study which highlights the effectiveness of the framework. This work adds to the existing literature on software aging and its preventative measures. It also fills in the research gap which exists about software aging caused by changing requirements.

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Section: Related Workmentioning

confidence: 99%

A Simple Software Rejuvenation Framework Based on Model Driven Development

Mahmud

2017

UHDJST

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“…Huang et al [17] proposed a three-state stochastic model, including a robust state, a failure-prone state and a failure state. This model was extended and studied in detail by other researchers to answer similar questions [9,10]. Chen et al [8] introduced a threshold to judge the current pattern of software aging and to describe its nonlinearity.…”

Section: Matias Et Al Used Design Of Experiments (Doe) and Acceleratementioning

confidence: 99%

Using Neural Networks to Forecast Available System Resources: An Approach and Empirical Investigation

Jia

Zhi

Xue³

et al. 2015

Int. J. Soft. Eng. Knowl. Eng.

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Software aging refers to the phenomenon that software systems show progressive performance degradation or a sudden crash after longtime execution. It has been reported that this phenomenon is closely related to the exhaustion of system resources. This paper quantitatively studies available system resources under the realworld situation where workload changes dynamically over time. We propose a neural network approach to first investigate the relationship between available system resources and system workload and then to forecast future available system resources. Experimental results on data sets collected from real-world computer systems demonstrate that the proposed approach is effective.

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“…On this basis, an optimized rejuvenation schedule is obtained. The tools used here include continuous-time Markov chain models [9], semi-Markov models [10], and others [11].…”

Section: Related Workmentioning

confidence: 99%

Managing Performance of Aging Applications Via Synchronized Replica Rejuvenation

Andrzejak

Moser

Silva

2007

Managing Virtualization of Networks and Services

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Abstract. We investigate the problem of ensuring and maximizing performance guarantees for applications suffering software aging. Our focus is the optimization of the minimum and average performance of such applications in virtualized and non-virtualized scenario. The key technique is to use a set of simultaneously active application replica and to optimize their rejuvenation schedules. We derive an analytical method for maximizing the minimum "any-time" performance for certain cases and propose a heuristic method for maximization of minimum and average performance for all others. To evaluate our method we perform extensive studies on two applications: aging profiles of Apache Axis 1.3 and the aging data of the TPC-W benchmark instrumented with a memory leak injector. The results show that our approach is a practical way to ensure uninterrupted availability and optimize performance for even strongly aging applications.

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Statistical non-parametric algorithms to estimate the optimal software rejuvenation schedule

Cited by 81 publications

References 9 publications

A Simple Software Rejuvenation Framework Based on Model Driven Development

A Simple Software Rejuvenation Framework Based on Model Driven Development

Using Neural Networks to Forecast Available System Resources: An Approach and Empirical Investigation

Managing Performance of Aging Applications Via Synchronized Replica Rejuvenation

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