Service Availability Analysis in a Virtualized System: A Markov Regenerative Model Approach

Bai, Jing; Chang, Xiaolin; Ning, Gaorong; Zhang, Zhenjiang; Trivedi, Kishor S.

doi:10.1109/tcc.2020.3028648

Cited by 11 publications

(6 citation statements)

References 29 publications

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“…Machida et al [29] proposed SMP models to compare the effectiveness of time-based rejuvenation, time-based life-extension and hybrid approaches, from the aspects of job completion time and system availability. Based on Markov regenerative process (MRGP), the authors in [30] studied the service availability in the VM-based system, in which application service, VM and virtual machine monitor (VMM) can experience resource degradation. They in [31] presented an SMP model to analyze the vehicle platooning service resilience.…”

Section: Analytical Modelingmentioning

confidence: 99%

“…They further in [32] analyzed the impact of VNF aging on the dependability on MEC-SFC services. These model in [30]- [32] did not capture the time-dependent behaviors between the subservices and the Host OSes that run them. These studies [24]- [32] ignored time-dependent behaviors between VNFs, between Host OSes, and between VNFs and Host OSes.…”

Section: Analytical Modelingmentioning

confidence: 99%

“…These studies [24]- [32] ignored time-dependent behaviors between VNFs, between Host OSes, and between VNFs and Host OSes. In addition, some studies [24][25][27]- [30] evaluated only one or two aspects of reliability, steady-state availability and transient availability. Unlike them, we consider a two-tier (VNF and Host OS) UMEC system, in which VNF restart and failover techniques are deployed for rejuvenation at the VNF level, and OS reboot and live container migration are deployed for rejuvenation at the Host OS level.…”

Section: Analytical Modelingmentioning

confidence: 99%

“…They often assumed that all time intervals between events were N 2 > REPLACE THIS LINE WITH YOUR MANUSCRIPT ID NUMBER (DOUBLE-CLICK HERE TO EDIT) < exponentially distributed [26]- [28] and ignored time-dependent behaviors between VNFs and host OSes [26]- [32]. In addition, many studies only evaluated one of transient availability, steady-state availability and reliability [27]- [30]. Therefore, there are still some issues to be solved when assessing the resilience of UMEC service chains.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Towards UAV-Based MEC Service Chain Resilience Evaluation: A Quantitative Modeling Approach

Bai

Chang

Rodríguez

et al. 2023

IEEE Trans. Veh. Technol.

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Unmanned aerial vehicle (UAV) and network function virtualization (NFV) facilitate the deployment of multiaccess edge computing (MEC). In the UAV-based MEC (UMEC) network, virtualized network function (VNF) can be implemented as a lightweight container running on UMEC host operating system (OS). However, UMEC network is vulnerable to attack, which can result in resource degradation and even UMEC service disruption. Rejuvenation techniques, such as failover technique and live container migration technique, can mitigate the impact of resource degradation but their effectiveness to improve the resilience of UMEC services should be evaluated. This paper presents a quantitative modeling approach based on semi-Markov process to investigate the resilience of a UMEC service chain consisting of any number of VNFs executed in any number of UMEC hosts in terms of availability and reliability. Unlike existing studies, the semi-Markov model constructed in this paper can capture the time-dependent behaviors between VNFs, between host OSes, and between VNFs and host OSes on the condition that the holding times of the recovery and failure events follow any kind of distribution. We perform the sensitivity analysis to identify potential resilience bottlenecks. The results highlight that migration time is the parameter significantly affecting the resilience, which shed the insight on designing the UMEC service chain with high-grade resilience requirements. In addition, we carry out the numerical experiments to reveal that: (i) the type of failure time distribution has a significant effect on the resilience; and (ii) the resilience increases with decreasing number of VNFs, while the availability increases with increasing number of UMEC hosts and the reliability decreases with increasing number of UMEC hosts, which can provide meaningful guidance for the UAV placement optimization in the UMEC network.

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Section: Analytical Modelingmentioning

confidence: 99%

Section: Analytical Modelingmentioning

confidence: 99%

Section: Analytical Modelingmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Towards UAV-Based MEC Service Chain Resilience Evaluation: A Quantitative Modeling Approach

Bai

Chang

Rodríguez

et al. 2023

IEEE Trans. Veh. Technol.

Self Cite

View full text Add to dashboard Cite

show abstract

“…They evaluated the job completion time and service availability. They in [24] analyzed the optimal inspection time interval for maximizing CS availability based on Markov regenerative process (MRGP). They further evaluated the resilience, reliability and security of vehicle platooning service in [25] and analyzed the imapact of service function aging on the service dependability in [26].…”

Section: Related Workmentioning

confidence: 99%

Quantitative understanding serial-parallel hybrid sfc services: a dependability perspective

Bai

Chang

Machida

et al. 2022

Peer-to-Peer Netw. Appl.

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Container technology, as the key enabler behind microservice architectures, is widely applied in Cloud and Edge Computing. A long and continuous running of operating system (OS) hosting container-based services can encounter software aging that leads to performance deterioration and even causes system failures. OS rejuvenation techniques can mitigate the impact of software aging but the rejuvenation trigger interval needs to be carefully determined to reduce the downtime cost due to rejuvenation. This paper proposes a comprehensive semi-Markovbased approach to quantitatively evaluate the effect of OS rejuvenation on the dependability and the performance of a container-based service. In contrast to the existing studies, we neither restrict the distributions of time intervals of events to be exponential nor assume that backup resources are always available. Through the numerical study, we show the optimal container-migration trigger intervals that can maximize the dependability or minimize the performance of a container-based service.

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A Markov Regenerative Process Model for the Dependability and Performance of a Two-Unit Multi-State System under Maintenance

Koutras

2023

Reliability Engineering & System Safety

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Service Availability Analysis in a Virtualized System: A Markov Regenerative Model Approach

Cited by 11 publications

References 29 publications

Towards UAV-Based MEC Service Chain Resilience Evaluation: A Quantitative Modeling Approach

Towards UAV-Based MEC Service Chain Resilience Evaluation: A Quantitative Modeling Approach

Quantitative understanding serial-parallel hybrid sfc services: a dependability perspective

A Markov Regenerative Process Model for the Dependability and Performance of a Two-Unit Multi-State System under Maintenance

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