Automatic selection and composition of model transformations alternatives using evolutionary algorithms

Rahmoun, Smail; Borde, Étienne; Pautet, Laurent

doi:10.1145/2797433.2797459

Cited by 6 publications

(3 citation statements)

References 17 publications

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“…Mean Value Analysis was used to obtain the response time in a stationary state. A similar approach was also employed in [60], where multi-objective evolutionary algorithms have been used to optimize performance and reliability of system expressed through AADL models. Menascé et al [48] proposed to optimize performance and availability of service-based information systems by applying a hill-climbing optimization method.…”

Section: Design-time Approachesmentioning

confidence: 99%

QoS-Based Elasticity for Service Chains in Distributed Edge Cloud Environments

Cardellini

Grbac

Nardelli

et al. 2018

Lecture Notes in Computer Science

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With the emerging IoT and Cloud-based networked systems that rely heavily on virtualization technologies, elasticity becomes a dominant system engineering attribute for providing QoS-aware services to their users. Although the concept of elasticity can introduce significant QoS and cost benefits, its implementation in real systems is full of challenges. Indeed, nowadays systems are mainly distributed, built upon several layers of abstraction, and with centralized control mechanisms. In such a complex environment, controlling elasticity in a centralized manner might strongly penalize scalability. To overcome this issue, we can conveniently split the system in autonomous subsystems that implement elasticity mechanisms and run control policies in a decentralized manner. To efficiently and effectively cooperate with each other, the subsystems need to communicate among themselves to determine elasticity decisions that collectively improve the overall system performance. This new architecture calls for the development of new mechanisms and efficient policies. In this chapter, we focus on elasticity in IoT and Cloud-based systems, which can be geo-distributed also at the edge of the networks, and discuss its engineering perspectives along with various coordination mechanisms. We focus on the design choices that may affect the elasticity properties and provide an overview of some decentralized design patterns related to the coordination of elasticity decisions.

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Section: Design-time Approachesmentioning

confidence: 99%

QoS-Based Elasticity for Service Chains in Distributed Edge Cloud Environments

Cardellini

Grbac

Nardelli

et al. 2018

Lecture Notes in Computer Science

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“…The second paper [9], presented by Smail Rahmoun, focused on making trade-offs between non-functional properties when presented various design alternatives for software architectures. Therefore, Rahmoun et al formalize these design alternatives with model transformations, use evolutionary algorithms to create model transformation alternatives and finally identify the transformation that represents the best trade-off between the non-functional properties at hand.…”

Section: Automatic Selection and Composition Of Model Transformationsmentioning

confidence: 99%

“…After the non-functional properties of all alternatives are evaluated, a new generation of offspring is created using the evolutionary operation mutation and crossover. Finally, the output of the method presented in [9] is a set of nearly optimal AADL models. The authors demonstrate their approach in a use case with the goal of finding the optimal deployment of interconnected software components on hardware components.…”

Section: Automatic Selection and Composition Of Model Transformationsmentioning

confidence: 99%

Variability for Qualities in Software Architecture

Alebrahim

Faßbender

Filipczyk

et al. 2016

SIGSOFT Softw. Eng. Notes

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Variability is a key factor of most systems. While there are many works covering variability in functionality, there is a research gap regarding variability in software qualities. There is an obvious imbalance between the importance of variability in the context of quality attributes, and the intensity of research in this area. To improve this situation, the First International Workshop on VAriability for QUalIties in SofTware Architecture (VAQUITA) was held jointly with ECSA 2015 in Cavtat/Dubrovnik, Croatia as a one-day workshop. The goal of VAQUITA was to investigate and stimulate the discourse about the matter of variability, qualities, and software architectures. The workshop featured three research paper presentations, one keynote talk, and two working group discussions. In this workshop report, we summarize the keynote talk and the presented papers. Additionally, we present the results of the working group discussions.

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Surrogate Model Assisted Multi-objective Differential Evolution Algorithm for Performance Optimization at Software Architecture Level*

Xiaobin

et al. 2017

Lecture Notes in Computer Science

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Automatic selection and composition of model transformations alternatives using evolutionary algorithms

Cited by 6 publications

References 17 publications

QoS-Based Elasticity for Service Chains in Distributed Edge Cloud Environments

QoS-Based Elasticity for Service Chains in Distributed Edge Cloud Environments

Variability for Qualities in Software Architecture

Surrogate Model Assisted Multi-objective Differential Evolution Algorithm for Performance Optimization at Software Architecture Level*

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