Modeling and Analysis of High Availability Techniques in a Virtualized System

Chang, Xiaolin; Wang, Tianju; Rodríguez, Ricardo J.; Zhang, Zhenjiang

doi:10.1093/comjnl/bxx049

Cited by 13 publications

(11 citation statements)

References 26 publications

(52 reference statements)

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“…The past years witnessed significant efforts made for analytical model-based evaluation of AS availability and/or job completion time. See [13], [22]- [31] and references therein.…”

Section: Related Workmentioning

confidence: 99%

“…Virtual machine monitor (VMM), which can allow multiple VMs to share the same physical machine safely [12], plays a critical role in an SV-based system. However, it is software and then is subject to software aging [13] (a phenomenon of software performance degradation after a long continuous running [14]) and crash due to certain elusive faults [15]. That is, software aging can degrade application service (AS) availability (which is defined as percentage of normal service provision time for the system, in other words, percentage of system available time) and then degrade user Quality of Experience.…”

Section: Introductionmentioning

confidence: 99%

“…In this paper, we consider an SV-based system composed of hosts for executing a job and supporting live VM migration among the hosts. VMM, running in every host, is software that is subject to software aging after a long continuous running [13]. The system deploys VMM reboot and live VM migration techniques based on the time-based rejuvenation after software aging detection.…”

Section: Introductionmentioning

confidence: 99%

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Analyzing Software Rejuvenation Techniques in a Virtualized System: Service Provider and User Views

et al. 2020

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Virtualization technology has promoted the fast development and deployment of cloud computing, and is now becoming an enabler of Internet of Everything. Virtual machine monitor (VMM), playing a critical role in a virtualized system, is software and hence it suffers from software aging after a long continuous running as well as software crashes due to elusive faults. Software rejuvenation techniques can be adopted to reduce the impact of software aging. Although there existed analytical model-based approaches for evaluating software rejuvenation techniques, none analyzed both application service (AS) availability and job completion time in a virtualized system with live virtual machine (VM) migration. This paper aims to quantitatively analyze software rejuvenation techniques from service provider and user views in a virtualized system deploying VMM reboot and live VM migration techniques for rejuvenation, under the condition that all the aging time, failure time, VMM fixing time and live VM migration time follow general distributions. We construct an analytical model by using a semi-Markov process (SMP) and derive formulas for calculating AS availability and job completion time. By analytical experiments, we can obtain the optimal migration trigger intervals for achieving the approximate maximum AS availability and the approximate minimum job completion time, and then service providers can make decisions for maximizing the benefits of service providers and users by adjusting parameter values.

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“…The past years witnessed significant efforts made for analytical model-based evaluation of AS availability and/or job completion time. See [13], [22]- [31] and references therein.…”

Section: Related Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Analyzing Software Rejuvenation Techniques in a Virtualized System: Service Provider and User Views

et al. 2020

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“…Monolithic analytical models for investigating the availability of virtualized systems with detailed failures have been proposed [14], [15]. These models focused on the evaluation of VM and assumed all PMs are homogeneous.…”

Section: Model-based For Cdc Availabilitymentioning

confidence: 99%

Model-based sensitivity analysis of IaaS cloud availability

Liu

Chang

Han

et al. 2018

Future Generation Computer Systems

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The increasing shift of various critical services towards Infrastructure-as-a-Service (IaaS) cloud data centers (CDCs) creates a need for analyzing CDCs' availability, which is affected by various factors including repair policy and system parameters. This paper aims to apply analytical modeling and sensitivity analysis techniques to investigate the impact of these factors on the availability of a large-scale IaaS CDC, which (1) consists of active and two kinds of standby physical machines (PMs), (2) allows PM moving among active and two kinds of standby PM pools, and (3) allows active and two kinds of standby PMs to have different mean repair times. Two repair policies are considered: (P1) all pools share a repair station and (P2) each pool uses its own repair station. We develop monolithic availability models for each repair policy by using Stochastic Reward Nets and also develop the corresponding scalable two-level models in order to overcome the monolithic model's limitations, caused by the large-scale feature of a CDC and the complicated interactions among CDC components. We also explore how to apply differential sensitivity analysis technique to conduct parametric sensitivity analysis in the case of interacting submodels. Numerical results of monolithic models and simulation results are used to verify the approximate accuracy of interacting sub-models, which are further applied to examine the sensitivity of the large-scale CDC availability with respect to repair policy and system parameters.

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“…The tremendous increase in the number of vulnerabilities discovered and disclosed and the severity of their damage have prompted various research to the survivability modeling and analysis in various fields and from different perspectives [1] [6] [7] and the references therein. Recently, the authors in [1] carried out a quantitative assessment of the system secure survivability.…”

Section: IImentioning

confidence: 99%

Survivability Model for Security and Dependability Analysis of a Vulnerable Critical System

Chang

Rodríguez³

et al. 2018

2018 27th International Conference on Computer Communication and Networks (ICCCN)

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This paper aims to analyze transient security and dependability of a vulnerable critical system, under vulnerability-related attack and two reactive defense strategies, from a severe vulnerability announcement until the vulnerability is fully removed from the system. By severe, we mean that the vulnerability-based malware could cause significant damage to the infected system in terms of security and dependability while infecting more and more new vulnerable computer systems. We propose a Markov chain-based survivability model for capturing the vulnerable critical system behaviors during the vulnerability elimination process. A high-level formalism based on Stochastic Reward Nets is applied to automatically generate and solve the survivability model. Survivability metrics are defined to quantify system attributes. The proposed model and metrics not only enable us to quantitatively assess the system survivability in terms of security risk and dependability, but also provide insights on the system investment decision. Numerical experiments are constructed to study the impact of key parameters on system security, dependability and profit.

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Modeling and Analysis of High Availability Techniques in a Virtualized System

Cited by 13 publications

References 26 publications

Analyzing Software Rejuvenation Techniques in a Virtualized System: Service Provider and User Views

Analyzing Software Rejuvenation Techniques in a Virtualized System: Service Provider and User Views

Model-based sensitivity analysis of IaaS cloud availability

Survivability Model for Security and Dependability Analysis of a Vulnerable Critical System

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