Empirical resilience evaluation of an architecture-based self-adaptive software system

Cámara, Javier; Correia, Pedro Pezarat; Lemos, Rogério de; Vieira, Marco

doi:10.1145/2602576.2602577

Cited by 18 publications

(9 citation statements)

References 30 publications

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“…They distinguish between 'nominal' and 'self-*' situations and their relations: The approach determines the effort by comparing the operation time with the adaptation time. Some of the developed metrics have been investigated in detail by Camara et al for software architecture scenarios [Cámara et al (2014)]. Besides, success and adaptation efforts and ways to measure autonomy have been investigated, see e.g.…”

Section: Self-adaptation Based Measuresmentioning

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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Section: Self-adaptation Based Measuresmentioning

confidence: 99%

A Quantification Approach for Transferability in Lifelike Computing Systems

Goller¹,

Tomforde²

2023

Preprint

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“…For instance, they measure the operation time about the adaptation time to determine the effort. Some of the developed metrics have been investigated in detail by Camara et al for software architecture scenarios [17]. Moreover, success and adaptation efforts and ways to measure autonomy have been investigated, see e.g., [18].…”

Section: State Of the Artmentioning

confidence: 99%

To Adapt or Not to Adapt: A Quantification Technique for Measuring an Expected Degree of Self-Adaptation

Tomforde

Goller

2020

Computers

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Self-adaptation and self-organization (SASO) have been introduced to the management of technical systems as an attempt to improve robustness and administrability. In particular, both mechanisms adapt the system's structure and behavior in response to dynamics of the environment and internal or external disturbances. By now, adaptivity has been considered to be fully desirable. This position paper argues that too much adaptation conflicts with goals such as stability and user acceptance. Consequently, a kind of situation-dependent degree of adaptation is desired, which defines the amount and severity of tolerated adaptations in certain situations. As a first step into this direction, this position paper presents a quantification approach for measuring the current adaptation behavior based on generative, probabilistic models. The behavior of this method is analyzed in terms of three application scenarios: urban traffic control, the swidden farming model, and data communication protocols. Furthermore, we define a research roadmap in terms of six challenges for an overall measurement framework for SASO systems.

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“…LGZLogistics requirements for mitigation. However, an accurate probability can only be achieved through rigorous benchmarking of the scenario in an off-line environment [10]. In any case, probabilities defined are specific to the deployment environment, and configuration of the authorisation infrastructure.…”

Section: Probabilities Cited Are Pseudo Values That Indicatementioning

confidence: 99%