元宇宙应用可靠性分析研究
On Metaverse Application Dependability Analysis
AI总结：
针对元宇宙服务功能及相关软硬件组件老化导致应用可靠性下降的问题，构建基于半马尔可夫过程和可靠性框图的分层模型，分析老化与复壮技术的影响并识别关键影响参数。
摘要：
元宇宙即服务（Metaverse as-a-Service，MaaS）支持元宇宙租户通过以元宇宙服务功能（Metaverse service functions，MSF）的形式分配元宇宙资源，来运行其应用程序（MetaAPP）。通常，每个MSF都部署在虚拟机（virtual machine，VM）中，以获得更好的弹性和安全性。然而，这些MSF以及运行它们的虚拟机和虚拟机监视器（virtual machine monitors，VMM）在长时间连续运行后可能会出现软件老化问题，进而导致MetaAPP可靠性下降，也就是由分配给MetaAPP的MSF组成的MSF链（MSF chain，MSFC）的可靠性下降。本文旨在研究在活动组件（MSF、VM和VMM）及其备用组件均会受到软件老化影响的场景下，软件老化与软件复壮技术对MetaAPP可靠性的影响。我们应用半马尔可夫过程和可靠性框图，构建了一个分层模型来刻画老化、故障和恢复的行为。我们开展了数值分析与仿真实验，以评估所提模型的近似精度和可靠性指标。随后，我们通过敏感性分析确定了提升MetaAPP/MSFC可靠性的关键参数，同时还研究了各类参数对MetaAPP/MSFC可靠性的影响。
英文摘要：
Metaverse as-a-Service (MaaS) enables Metaverse tenants to execute their APPlications (MetaAPP) by allocating Metaverse resources in the form of Metaverse service functions (MSF). Usually, each MSF is deployed in a virtual machine (VM) for better resiliency and security. However, these MSFs along with VMs and virtual machine monitors (VMM) running them may encounter software aging after prolonged continuous operation. Then, there is a decrease in MetaAPP dependability, namely, the dependability of the MSF chain (MSFC), consisting of MSFs allocated to MetaAPP. This paper aims to investigate the impact of both software aging and rejuvenation techniques on MetaAPP dependability in the scenarios, where both active components (MSF, VM and VMM) and their backup components are subject to software aging. We develop a hierarchical model to capture behaviors of aging, failure, and recovery by applying Semi-Markov process and reliability block diagram. Numerical analysis and simulation experiments are conducted to evaluate the approximation accuracy of the proposed model and dependability metrics. We then identify the key parameters for improving the MetaAPP/MSFC dependability through sensitivity analysis. The investigation is also made about the influence of various parameters on MetaAPP/MSFC dependability.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
