Adaptive Fault Detection Exploiting Redundancy with Uncertainties in Space and Time

Ratasich, Denise; Platzer, Michael; Grosu, Radu; Bartocci, Ezio

doi:10.1109/saso.2019.00013

Cited by 6 publications

(2 citation statements)

References 31 publications

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“…Replication methods are particularly applicable in multi-agent systems, for instance, group replication via proxy servers [13], replication of agents based on the criticality of their planned actions [16], adjustable group replication with a leader agents [14] or introducing a special class of agents for redundancy maintenance [20]. New replication strategies designed for the Internet of Things and cyber-physical systems are subject of recent work [21], [22]. Self-healing methods [23] can be preventive (proactive) [12] or reactive (resilient) [11].…”

Section: Positioning and Comparison To Related Workmentioning

confidence: 99%

Self-Healing Dilemmas in Distributed Systems: Fault Correction vs. Fault Tolerance

Nikolic

Jubatyrov

Pournaras

2021

IEEE Trans. Netw. Serv. Manage.

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Large-scale decentralized systems of autonomous agents interacting via asynchronous communication often experience the following self-healing dilemma: fault detection inherits network uncertainties making a remote faulty process indistinguishable from a slow process. In the case of a slow process without fault, fault correction is undesirable as it can trigger new faults that could be prevented with fault tolerance that is a more proactive system maintenance. But in the case of an actual faulty process, fault tolerance alone without eventually correcting persistent faults can make systems underperforming. Measuring, understanding and resolving such self-healing dilemmas is a timely challenge and critical requirement given the rise of distributed ledgers, edge computing, the Internet of Things in several energy, transport and health applications. This paper contributes a novel and general-purpose modeling of fault scenarios during system runtime. They are used to accurately measure and predict inconsistencies generated by the undesirable outcomes of fault correction and fault tolerance as the means to improve selfhealing of large-scale decentralized systems at the design phase. A rigorous experimental methodology is designed that evaluates 696 experimental settings of different fault scales, fault profiles and fault detection thresholds in a prototyped decentralized network of 3000 nodes. Almost 9 million measurements of inconsistencies were collected in a network, where each node monitors the health status of another node, while both can defect. The prediction performance of the modeled fault scenarios is validated in a challenging application scenario of decentralized and dynamic in-network data aggregation using real-world data from a Smart Grid pilot project. Findings confirm the origin of inconsistencies at design phase and provide new insights how to tune self-healing at an early stage. Strikingly, the aggregation accuracy is well predicted as shown by high correlations and low root mean square errors.

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Section: Positioning and Comparison To Related Workmentioning

confidence: 99%

Self-Healing Dilemmas in Distributed Systems: Fault Correction vs. Fault Tolerance

Nikolic

Jubatyrov

Pournaras

2021

IEEE Trans. Netw. Serv. Manage.

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show abstract

“…Replication methods are particularly applicable in multi-agent systems, for instance, group replication via proxy servers [13], replication of agents based on the criticality of their planned actions [20], adjustable group replication with a leader agents [18] or introducing a special class of agents for redundancy maintenance [24]. New replication strategies designed for the Internet of Things and cyber-physical systems are subject of recent work [25], [26]. Self-healing methods [27] can be preventive (proactive) [12] or reactive (resilient) [17].…”

Section: Positioning and Comparison To Related Workmentioning

confidence: 99%

Self-healing Dilemmas in Distributed Systems: Fault Correction vs. Fault Tolerance

Nikolić¹,

Jubatyrov²,

Pournaras³

2020

Preprint

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Large-scale decentralized systems of autonomous agents interacting via asynchronous communication often experience the following self-healing dilemma: Fault-detection inherits network uncertainties making a faulty process indistinguishable from a slow process. The implications can be dramatic: Self-healing mechanisms become biased and cost-ineffective. In particular, triggering an undesirable fault-correction results in new faults that could be prevented with fault-tolerance instead. Nevertheless, fault-tolerance alone without eventually correcting persistent faults makes systems underperforming as well. Measuring, understanding and resolving such self-healing dilemmas is a timely challenge and critical requirement given the rise of distributed ledgers, edge computing, the Internet of Things in several application domains of energy, transport and health. This paper introduces a novel and general-purpose modeling of fault scenarios. They can accurately measure and predict inconsistencies generated by fault-correction and fault-tolerance when each node in a network can monitor the health status of another node, while both can defect. In contrast to related work, no information about the computational/application scenario, overlying algorithms or application data is required. A rigorous experimental methodology is designed that evaluates 696 experimental settings of different fault scales, fault profiles and fault detection thresholds, each with almost 9 million measurements of inconsistencies in a prototyped decentralized network of 3000 nodes. The prediction performance of the modeled fault scenarios is validated in a challenging application scenario of decentralized and dynamic in-network aggregation using real-world data from a Smart Grid pilot project. Findings confirm the origin of inconsistencies at design phase and provide new insights how to tune self-healing mechanisms at design phase. Strikingly, the aggregation accuracy is well predicted as shown by high correlations and low root mean square errors when calibration methods with application-independent features are applied.

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A Review and Analysis of the Characteristics of Cyber-physical Systems in Industry 4.0

Eslami,

Franciosi,

Ashouri

et al. 2023

SN COMPUT. SCI.

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Adaptive Fault Detection Exploiting Redundancy with Uncertainties in Space and Time

Cited by 6 publications

References 31 publications

Self-Healing Dilemmas in Distributed Systems: Fault Correction vs. Fault Tolerance

Self-Healing Dilemmas in Distributed Systems: Fault Correction vs. Fault Tolerance

Self-healing Dilemmas in Distributed Systems: Fault Correction vs. Fault Tolerance

A Review and Analysis of the Characteristics of Cyber-physical Systems in Industry 4.0

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