The aggressive waves of ongoing world-wide virus pandemics urge us to conduct further studies on the performability of local computing infrastructures at hospitals/medical centers to provide a high level of assurance and trustworthiness of medical services and treatment to patients, and to help diminish the burden and chaos of medical management and operations. Previous studies contributed tremendous progress on the dependability quantification of existing computing paradigms (e.g., cloud, grid computing) at remote data centers, while a few works investigated the performance of provided medical services under the constraints of operational availability of devices and systems at local medical centers. Therefore, it is critical to rapidly develop appropriate models to quantify the operational metrics of medical services provided and sustained by medical information systems (MIS) even before practical implementation. In this paper, we propose a comprehensive performability SRN model of an edge/fog based MIS for the performability quantification of medical data transaction and services in local hospitals or medical centers. The model elaborates different failure modes of fog nodes and their VMs under the implementation of fail-over mechanisms. Sophisticated behaviors and dependencies between the performance and availability of data transactions are elaborated in a comprehensive manner when adopting three main load-balancing techniques including: (i) probability-based, (ii) random-based and (iii) shortest queue-based approaches for medical data distribution from edge to fog layers along with/without fail-over mechanisms in the cases of component failures at two levels of fog nodes and fog virtual machines (VMs). Different performability metrics of interest are analyzed including (i) recover token rate, (ii) mean response time, (iii) drop probability, (iv) throughput, (v) queue utilization of network devices and fog nodes to assimilate the impact of load-balancing techniques and fail-over mechanisms. Discrete-event simulation results highlight the effectiveness of the combination of these for enhancing the performability of medical services provided by an MIS. Particularly, performability metrics of medical service continuity and quality are improved with fail-over mechanisms in the MIS while load balancing techniques help to enhance system performance metrics. The implementation of both load balancing techniques along with fail-over mechanisms provide better performability metrics compared to the separate cases. The harmony of the integrated strategies eventually provides the trustworthiness of medical services at a high level of performability. This study can help improve the design of MIS systems integrated with different load-balancing techniques and fail-over mechanisms to maintain continuous performance under the availability constraints of medical services with heavy computing workloads in local hospitals/medical centers, to combat with new waves of virus pandemics.

中文翻译：

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使用随机奖励网对具有边缘/雾计算的医疗信息系统进行负载平衡和故障转移策略的可实施性评估

持续的全球病毒大流行浪潮促使我们进一步研究医院/医疗中心本地计算基础设施的可操作性，以向患者提供医疗服务和治疗的高水平保证和可信度，并帮助减少医疗管理和运营的负担和混乱。先前的研究在远程数据中心现有计算范式（例如云计算、网格计算）的可靠性量化方面取得了巨大进展，而一些工作则调查了在本地医疗设备和系统操作可用性的限制下提供的医疗服务的性能。中心。所以，甚至在实际实施之前，快速开发适当的模型来量化医疗信息系统 (MIS) 提供和维持的医疗服务的运营指标至关重要。在本文中，我们提出了一种基于边缘/雾的 MIS 的综合可执行性 SRN​​ 模型，用于本地医院或医疗中心的医疗数据交易和服务的可执行性量化。该模型阐述了在故障转移机制实现下雾节点及其虚拟机的不同故障模式。在采用三种主要的负载平衡技术时，数据事务的性能和可用性之间的复杂行为和依赖关系将得到全面阐述，这些技术包括：(i) 基于概率、(ii) 基于随机和 (iii) 基于最短队列的医学数据从边缘到雾层分布的方法，以及在雾节点和雾虚拟机 (VM) 两级组件故障的情况下，有/没有故障转移机制）。分析了不同的感兴趣的性能指标，包括 (i) 恢复令牌率，(ii) 平均响应时间，(iii) 丢弃概率，(iv) 吞吐量，(v) 网络设备和雾节点的队列利用率以吸收负载的影响- 平衡技术和故障转移机制。离散事件模拟结果突出了这些组合在提高 MIS 提供的医疗服务的可执行性方面的有效性。特别，医疗服务连续性和质量的可执行性指标通过 MIS 中的故障转移机制得到改善，而负载平衡技术有助于增强系统性能指标。与单独的情况相比，负载平衡技术和故障转移机制的实现提供了更好的性能指标。整合策略的协调最终以高水平的可执行性提供了医疗服务的可信度。这项研究可以帮助改进集成了不同负载平衡技术和故障转移机制的 MIS 系统的设计，以在当地医院/医疗中心计算工作负载繁重的医疗服务的可用性限制下保持持续性能，以应对新一波的病毒大流行。