000125347 001__ 125347
000125347 005__ 20241125101135.0
000125347 0247_ $$2doi$$a10.1109/TVT.2022.3225564
000125347 0248_ $$2sideral$$a133115
000125347 037__ $$aART-2023-133115
000125347 041__ $$aeng
000125347 100__ $$aBai, J.
000125347 245__ $$aTowards UAV-based MEC service chain resilience evaluation: a quantitative modeling approach
000125347 260__ $$c2023
000125347 5060_ $$aAccess copy available to the general public$$fUnrestricted
000125347 5203_ $$aUnmanned 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.
000125347 536__ $$9info:eu-repo/grantAgreement/ES/DGA-UZ/T21-20R
000125347 540__ $$9info:eu-repo/semantics/openAccess$$aAll rights reserved$$uhttp://www.europeana.eu/rights/rr-f/
000125347 590__ $$a6.1$$b2023
000125347 592__ $$a2.714$$b2023
000125347 591__ $$aENGINEERING, ELECTRICAL & ELECTRONIC$$b45 / 353 = 0.127$$c2023$$dQ1$$eT1
000125347 591__ $$aTRANSPORTATION SCIENCE & TECHNOLOGY$$b12 / 72 = 0.167$$c2023$$dQ1$$eT1
000125347 591__ $$aTELECOMMUNICATIONS$$b15 / 119 = 0.126$$c2023$$dQ1$$eT1
000125347 593__ $$aAerospace Engineering$$c2023$$dQ1
000125347 593__ $$aApplied Mathematics$$c2023$$dQ1
000125347 593__ $$aComputer Networks and Communications$$c2023$$dQ1
000125347 593__ $$aElectrical and Electronic Engineering$$c2023$$dQ1
000125347 593__ $$aAutomotive Engineering$$c2023$$dQ1
000125347 594__ $$a13.0$$b2023
000125347 655_4 $$ainfo:eu-repo/semantics/article$$vinfo:eu-repo/semantics/acceptedVersion
000125347 700__ $$aChang, X.
000125347 700__ $$0(orcid)0000-0001-7982-0359$$aRodríguez, Ricardo J.$$uUniversidad de Zaragoza
000125347 700__ $$aTrivedi, K. S.
000125347 700__ $$aLi, S.
000125347 7102_ $$15007$$2570$$aUniversidad de Zaragoza$$bDpto. Informát.Ingenie.Sistms.$$cÁrea Lenguajes y Sistemas Inf.
000125347 773__ $$g72, 4 (2023), 5181 - 5194$$pIEEE trans. veh. technol.$$tIEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY$$x0018-9545
000125347 8564_ $$s1526199$$uhttps://zaguan.unizar.es/record/125347/files/texto_completo.pdf$$yPostprint
000125347 8564_ $$s3782811$$uhttps://zaguan.unizar.es/record/125347/files/texto_completo.jpg?subformat=icon$$xicon$$yPostprint
000125347 909CO $$ooai:zaguan.unizar.es:125347$$particulos$$pdriver
000125347 951__ $$a2024-11-22-12:00:32
000125347 980__ $$aARTICLE