Beyond Homeostasis: A Novel Approach for Assessing the Stability and Coherence of Self-Adaptive Systems

Tomforde, Sven; Goller, Martin

doi:10.1109/dasc-picom-cbdcom-cyberscitech52372.2021.00018

Cited by 5 publications

(6 citation statements)

References 27 publications

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“…Architectural Resilience metrics are, instead, the core of the work by Cámara et al [28], where 13 metrics are presented, specifically used to show the evidence of the beneficial impact of architecture-based self-adaptation on resilience with respect to different approaches, such as those relying on code-based adaptation. Lastly, Tomforde and Goller in their recent works [32], [33] provide metrics for measuring the Configuration & Adaptation and Global & Avg. Parameter Spectrum Usage, respectively, as we will better discuss later on in this section.…”

Section: Related Workmentioning

confidence: 99%

“…Eventually, only a few papers (i.e., [32], [33], [34], [35], [36], [37], [38], [39], [40], [41], [42], [43]) fulfilled the criteria and were evaluated. Hartsell et al [34] present ReSonAte, a dynamic risk estimation and assessment framework for autonomous systems.…”

Section: Related Workmentioning

confidence: 99%

“…The studies by Tomforde and Goller [32], [33] extend an existing measurement framework for the properties of adaptive systems, by defining new metrics. Metrics measuring the quantification of parameters utilization, under dynamic conditions.…”

Section: Related Workmentioning

confidence: 99%

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Evaluation Framework for Autonomous Systems: The Case of Programmable Electronic Medical Systems

Bombarda,

Bonfanti,

De Sanctis

et al. 2024

IIEEE Trans. Software Eng.

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This paper proposes an evaluation framework for autonomous systems, called LENS. It is an instrument to make an assessment of a system through the lens of abilities related to adaptation and smartness. The assessment can then help engineers understand in which direction it is worth investing to make their system smarter. It also helps to identify possible improvement directions and to plan for concrete activities. Finally, it helps to make a re-assessment when the improvement has been performed in order to check whether the activity plan has been accomplished. Given the high variability in the various domains in which autonomous systems are and can be used, LENS is defined in abstract terms and instantiated to a specific and important class of medical devices, i.e., Programmable Electronic Medical Systems (PEMS). The instantiation, called LENSPEMS, is validated in terms of applicability, i.e., how it is applicable to real PEMS, generalizability, i.e., to what extent LENSPEMS is generalizable to the PEMS class of systems, and usefulness, i.e., how it is useful in making an assessment and identifying possible directions of improvement towards smartness.

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Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

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Evaluation Framework for Autonomous Systems: The Case of Programmable Electronic Medical Systems

Bombarda,

Bonfanti,

De Sanctis

et al. 2024

IIEEE Trans. Software Eng.

View full text Add to dashboard Cite

show abstract

“…To answer that question, we need measurements to identify abnormal adaptation processes in the system. In previous work, we presented a few measures for that purpose: Configuration stability [Goller and Tomforde (2020)], configuration variability [Tomforde and Goller (2021a)], configuration coherence [Tomforde and Goller (2021b)] and parameter utilisation [Goller and Tomforde (2022)].…”

Section: Quantifying the Adaptation Behaviourmentioning

confidence: 99%

“…Therefore, a higher value means a higher coherence. See [Tomforde and Goller (2021b)] for more details.…”

Section: Configuration Stabilitymentioning

confidence: 99%

A Quantification Approach for Transferability in Lifelike Computing Systems

Goller¹,

Tomforde²

2023

Preprint

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The basic idea of lifelike computing systems is the transfer of concepts in living systems to technical use that goes even beyond existing concepts of self-adaptation and selforganisation (SASO). As a result, these systems become even more autonomous and changeable -up to a runtime transfer of the actual target function. Maintaining controllability requires a complete and dynamic (self-)quantification of the system behaviour with regard to aspects of SASO but also, in particular, lifelike properties. In this article, we discuss possible approaches for such metrics and establish a first metric for transferability. We analyse the behaviour of the metric using example applications and show that it is suitable for describing the system's behaviour at runtime.

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