Applying Model Transformations to Optimizing Real-Time QoS Configurations in DRE Systems

Kavimandan, A.; Gokhale, Aniruddha

doi:10.1007/978-3-642-02351-4_2

Cited by 11 publications

(6 citation statements)

References 25 publications

(23 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In our approach, however, architectural anti-pattern can be identified as side effect. In the context of distributed systems a rule based ap-proach for configuration optimization, according to QoS metrics, has been proposed in [49]. In [50] is proposed an approach that comprises a trade-off analysis of competing Non-Functional Requirements (NFR) in order to find critical components for one or 685 more NFR.…”

Section: Related Workmentioning

confidence: 99%

A mixed integer linear programming optimization approach for multi-cloud capacity allocation

Ciavotta

Ardagna

Gibilisco

2017

Journal of Systems and Software

View full text Add to dashboard Cite

The large success of the Cloud computing, its strong impact on the ICT world and on everyday life testifies the maturity and effectiveness this paradigm achieved in the last few years. Presently, the Cloud market offers a multitude of heterogeneous solutions; however, despite the undeniable advantages, Cloud computing introduced new issues and challenges. In particular, the heterogeneity of the available Cloud services and their pricing models makes the identification of a configuration that minimizes the operating costs of a Cloud application, guaranteeing at the same time the Quality of Service (QoS), a challenging task. This situation requires new processes and models to design software architectures (SAs) and predict costs and performance considering together the large variability in price models and the intrinsic dynamism and multi-tenancy of the Cloud environments. This work aims at providing a novel mathematical approach to this problem presenting a queueing theory based Mixed Integer Linear Program (MILP) to find a promising multi-cloud configuration for a given software architecture. The effectiveness of the proposed model has been favorably evaluated against first principle heuristics currently adopted by practitioners. Furthermore, the configuration returned by the model has been also used as initial solution for a local-search based optimization engine, which exploits more accurate but time-consuming performance models. This combined approach has been shown to improve the quality of the returned solutions by a 37% on average and reducing the overall search time by 50% with respect to state of the art heuristics based on tiers utilization thresholds.

show abstract

Section: Related Workmentioning

confidence: 99%

A mixed integer linear programming optimization approach for multi-cloud capacity allocation

Ciavotta

Ardagna

Gibilisco

2017

Journal of Systems and Software

View full text Add to dashboard Cite

show abstract

“…[14]) encapsulate general knowledge on how to improve system performance into executable rules; (ii) design space exploration approaches (e.g. [32]) explore the design space by examining alternatives that can cope with performance flaws; (iii) metaheuristic approaches (e.g.…”

Section: Related Workmentioning

confidence: 99%

A model-driven approach to broaden the detection of software performance antipatterns at runtime

Marco

Trubiani

2014

Electron. Proc. Theor. Comput. Sci.

View full text Add to dashboard Cite

Performance antipatterns document bad design patterns that have negative influence on system performance. In our previous work we formalized such antipatterns as logical predicates that build on four different views: (i) the static view that captures the software elements (e.g. classes, components) and the static relationships among them; (ii) the dynamic view that represents the interaction (e.g. messages) that occurs between the software elements to provide system functionalities; (iii) the deployment view that describes the hardware elements (e.g. processing nodes) and the mapping of software resources onto hardware platforms; (iv) the performance view that collects a set of specific performance indices. In this paper we present a lightweight infrastructure that enables the detection of software performance antipatterns at runtime through the monitoring of specific performance indices. The proposed approach precalculates the logical predicates of antipatterns and identifies the ones whose static, dynamic and deployment sub-predicates occur in the current system configuration and brings at runtime the verification of performance sub-predicates. The proposed infrastructure leverages model-driven techniques to generate probes for monitoring the performance sub-predicates thus to support the detection of antipatterns at runtime.

show abstract

“…Services are assumed to have fixed performance metrics that do not change for changing composition. Only service selection is considered as a degree of freedom, and trade-offs with other quality criteria are not considered Kavimandan et al [24] presents an approach to optimise component allocation in the context of distributed real-time embedded component-based systems. They enhance preexisting bin packing algorithms with the consideration of component consideration and deploy components together that have a compatible configuration.…”

Section: Related Workmentioning

confidence: 99%

Automatically improve software architecture models for performance, reliability, and cost using evolutionary algorithms

Martens

Koziolek²,

Becker

et al. 2010

Proceedings of the First Joint WOSP/SIPEW International Conference on Performance Engineering

143

View full text Add to dashboard Cite

Quantitative prediction of quality properties (i.e. extrafunctional properties such as performance, reliability, and cost) of software architectures during design supports a systematic software engineering approach. Designing architectures that exhibit a good trade-off between multiple quality criteria is hard, because even after a functional design has been created, many remaining degrees of freedom in the software architecture span a large, discontinuous design space. In current practice, software architects try to find solutions manually, which is time-consuming, can be errorprone and can lead to suboptimal designs. We propose an automated approach to search the design space for good solutions. Starting with a given initial architectural model, the approach iteratively modifies and evaluates architectural models. Our approach applies a multi-criteria genetic algorithm to software architectures modelled with the Palladio Component Model. It supports quantitative performance, reliability, and cost prediction and can be extended to other quantitative quality criteria of software architectures. We validate the applicability of our approach by applying it to an architecture model of a component-based business information system and analyse its quality criteria trade-offs by automatically investigating more than 1200 alternative design candidates.

show abstract

Applying Model Transformations to Optimizing Real-Time QoS Configurations in DRE Systems

Cited by 11 publications

References 25 publications

A mixed integer linear programming optimization approach for multi-cloud capacity allocation

A mixed integer linear programming optimization approach for multi-cloud capacity allocation

A model-driven approach to broaden the detection of software performance antipatterns at runtime

Automatically improve software architecture models for performance, reliability, and cost using evolutionary algorithms

Contact Info

Product

Resources

About