Dependability evaluation of a disaster recovery solution for IoT infrastructures

Andrade, Ermeson; Nogueira, Bruno

doi:10.1007/s11227-018-2290-0

Cited by 26 publications

(23 citation statements)

References 27 publications

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“…Among research on IoT dependability, we found five studies that present mathematical approaches to measuring system reliability and availability [79][80][81][82][83]. In contrast, two others propose a calculus to estimate a confidence score to sensors [41], [84], and users [85].…”

Section: ) Mathematical Approachmentioning

confidence: 99%

“…Redundancy is not limited to providing system data replication. It also includes connection replication using different communication technology on the same IoT device [82], [83]. For example, in case of a connection failure in the LPWAN interface, the device may use a Wi-Fi or 4G connection to reestablish communication with other nodes [92].…”

Section: ) Redundancymentioning

confidence: 99%

“…Availability ensures that the IoT system continues operating as long as possible. There are methods to keep the system available, like managing hardware redundancy [63], [82], and maintaining a fault management mechanism [58].…”

Section: ) System Availabilitymentioning

confidence: 99%

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A Survey on Trustworthiness for the Internet of Things

Ribeiro

Kamienski

2021

IEEE Access

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IoT systems use sensors to collect data from smart environments and manage resources through data analysis. An IoT system deals with many connected devices with different network and hardware constraints in a real-world scenario. An IoT system needs to handle low-latency data analysis, security threats, internal vulnerabilities, and network disconnections, which cause data loss and incorrect decisions. Trustworthiness (also known as dependability) provides various features for an IoT end-to-end data flow, such as resilience, security, availability, reliability, scalability, maintainability, heterogeneity, hardware resources management, fault management policies, and data quality. This paper presents a survey on trustworthiness and dependability in IoT systems and proposes the Trustworthiness for IoT Framework (TW-IoT) to provide trustworthiness at the data level for mist and fog-based IoT systems. The TW-IoT framework provides data trustworthiness to ensure a continuous and uninterrupted operation of IoT data flow. We also discuss challenges and trade-offs related to data trustworthiness in IoT.

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Section: ) Mathematical Approachmentioning

confidence: 99%

Section: ) Redundancymentioning

confidence: 99%

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A Survey on Trustworthiness for the Internet of Things

Ribeiro

Kamienski

2021

IEEE Access

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“…The work in Andrade and Nogueira [ 18 ] proposes a dependability evaluation approach based on stochastic Petri nets (SPN). That approach analyses disaster recovery solutions for IoT infrastructures, evaluating system reliability and availability, considering energy consumption and network communication.…”

Section: Related Workmentioning

confidence: 99%

A Comprehensive Dependability Model for QoM-Aware Industrial WSN When Performing Visual Area Coverage in Occluded Scenarios

Jesus

Portugal

Costa

et al. 2020

Sensors

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In critical industrial monitoring and control applications, dependability evaluation will be usually required. For wireless sensor networks deployed in industrial plants, dependability evaluation can provide valuable information, enabling proper preventive or contingency measures to assure their correct and safe operation. However, when employing sensor nodes equipped with cameras, visual coverage failures may have a deep impact on the perceived quality of industrial applications, besides the already expected impacts of hardware and connectivity failures. This article proposes a comprehensive mathematical model for dependability evaluation centered on the concept of Quality of Monitoring (QoM), processing availability, reliability and effective coverage parameters in a combined way. Practical evaluation issues are discussed and simulation results are presented to demonstrate how the proposed model can be applied in wireless industrial sensor networks when assessing and enhancing their dependability.

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“…The work highlighted the existing consideration of dependability metrics (availability, reliability) of fog computing systems, but the safety and security metrics and the trade-offs between dependability and security metrics have not been investigated in a complete manner. In another work [8], Andrade et al explored dependability of a cloud-based disaster recovery solution for e-health IoT infrastructure using stochastic petri net (SPN). The most recent works [9,10] on the availability and performance evaluation of IoT infrastructures considered the integration of cloud/fog/edge computing paradigms in an e-health system.…”

Section: Introductionmentioning

confidence: 99%

A Hierarchical Modeling and Analysis Framework for Availability and Security Quantification of IoT Infrastructures

2020

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Modeling a complete Internet of Things (IoT) infrastructure is crucial to assess its availability and security characteristics. However, modern IoT infrastructures often consist of a complex and heterogeneous architecture and thus taking into account both architecture and operative details of the IoT infrastructure in a monolithic model is a challenge for system practitioners and developers. In that regard, we propose a hierarchical modeling framework for the availability and security quantification of IoT infrastructures in this paper. The modeling methodology is based on a hierarchical model of three levels including (i) reliability block diagram (RBD) at the top level to capture the overall architecture of the IoT infrastructure, (ii) fault tree (FT) at the middle level to elaborate system architectures of the member systems in the IoT infrastructure, and (iii) continuous time Markov chain (CTMC) at the bottom level to capture detailed operative states and transitions of the bottom subsystems in the IoT infrastructure. We consider a specific case-study of IoT smart factory infrastructure to demonstrate the feasibility of the modeling framework. The IoT smart factory infrastructure is composed of integrated cloud, fog, and edge computing paradigms. A complete hierarchical model of RBD, FT, and CTMC is developed. A variety of availability and security measures are computed and analyzed. The investigation of the case-study’s analysis results shows that more frequent failures in cloud cause more severe decreases of overall availability, while faster recovery of edge enhances the availability of the IoT smart factory infrastructure. On the other hand, the analysis results of the case-study also reveal that cloud servers’ virtual machine monitor (VMM) and virtual machine (VM), and fog server’s operating system (OS) are the most vulnerable components to cyber-security attack intensity. The proposed modeling and analysis framework coupled with further investigation on the analysis results in this study help develop and operate the IoT infrastructure in order to gain the highest values of availability and security measures and to provide development guidelines in decision-making processes in practice.

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Dependability evaluation of a disaster recovery solution for IoT infrastructures

Cited by 26 publications

References 27 publications

A Survey on Trustworthiness for the Internet of Things

A Survey on Trustworthiness for the Internet of Things

A Comprehensive Dependability Model for QoM-Aware Industrial WSN When Performing Visual Area Coverage in Occluded Scenarios

A Hierarchical Modeling and Analysis Framework for Availability and Security Quantification of IoT Infrastructures

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