125347 20251113150203.0 doi 10.1109/TVT.2022.3225564 sideral 133115 ART-2023-133115 eng Bai, J. Towards UAV-based MEC service chain resilience evaluation: a quantitative modeling approach 2023 Access copy available to the general public Unrestricted Unmanned aerial vehicle (UAV) and network function virtualization (NFV) facilitate the deployment of multi-access 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. info:eu-repo/grantAgreement/ES/DGA-UZ/T21-20R info:eu-repo/semantics/openAccess All rights reserved http://www.europeana.eu/rights/rr-f/ 6.1 2023 ENGINEERING, ELECTRICAL & ELECTRONIC 45 / 353 = 0.127 2023 Q1 T1 TRANSPORTATION SCIENCE & TECHNOLOGY 12 / 72 = 0.167 2023 Q1 T1 TELECOMMUNICATIONS 15 / 119 = 0.126 2023 Q1 T1 2.714 2023 Aerospace Engineering 2023 Q1 Applied Mathematics 2023 Q1 Electrical and Electronic Engineering 2023 Q1 Computer Networks and Communications 2023 Q1 Automotive Engineering 2023 Q1 13.0 2023 info:eu-repo/semantics/article info:eu-repo/semantics/acceptedVersion Chang, X. Rodríguez, Ricardo J. Universidad de Zaragoza (orcid)0000-0001-7982-0359 Trivedi, K. S. Li, S. 5007 570 Universidad de Zaragoza Dpto. Informát.Ingenie.Sistms. Área Lenguajes y Sistemas Inf. 72, 4 (2023), 5181 - 5194 IEEE trans. veh. technol. IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY 0018-9545 1526199 http://zaguan.unizar.es/record/125347/files/texto_completo.pdf Postprint 3782811 http://zaguan.unizar.es/record/125347/files/texto_completo.jpg?subformat=icon icon Postprint oai:zaguan.unizar.es:125347 articulos driver 2025-11-13-15:00:43 ARTICLE