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13th IEEE World Congress on Services (SERVICES)

作者： Abrahao, Silvia Insfran, Emilio Univ Politecn Valencia Dept Comp Syst & Computat Camino Vera S-N E-46022 Valencia Spain

ISBN: (纸本)9781538620021

A number of monitoring approaches for cloud services have been proposed in the last years. However, they suffer from several limitations mainly due to changes in the monitoring requirements or because of the complexity in dealing with raw data from services at runtime. To address these problems, in a previous work, we proposed a platform-independent monitoring middleware for cloud services using models@runtime. This middleware was implemented in Microsoft Azure to monitor the quality of cloud services. To provide further evidence about the generalizability of our approach, in this work, we introduce the implementation of the monitoring middleware in the Google App Engine. The middleware gather raw data from the running cloud services to perform measurements that assess the compliance to the quality requirements established in a SLA. The use of models@runtime allowed us to provide a high-level of flexibility to change quality requirements at runtime.

关键词： Software as a Service Monitoring Middleware Quality of Service models@runtime Google App Engine

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Towards Meta-adaptation of Dynamic Adaptive Systems with models@runtime 5

Towards Meta-adaptation of Dynamic Adaptive Systems with Mod...

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5th International Conference on Model-Driven Engineering and Software Development (modelsWARD)

作者： Ferry, Nicolas Chauvel, Franck Song, Hui Solberg, Arnor SINTEF Oslo Norway

ISBN: (纸本)9789897582103

A models@runtime environment keeps a model in synchrony with a running system, this way a reasoning engine adapts the system by modifying this model. Existing models@runtime environments typically fail to let the user control what concepts form the model nor how the model is synchronised with the running system. This is yet mandatory in uncertain environments that are open, dynamic and heterogeneous. In this position paper we evolve the classical models@runtime architectural pattern to address this issue, together with some initial implementation results.

关键词： Model-driven Engineering models@runtime Dynamic Adaptive Systems

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Empirical Evaluation of a Method for Monitoring Cloud Services Based on models at runtime

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IEEE ACCESS 2021年 9卷 55898-55919页

作者： Cedillo, Priscila Insfran, Emilio Abrahao, Silvia Vanderdonckt, Jean Univ Cuenca Dept Comp Sci Cuenca 010203 Ecuador Univ Politecn Valencia Dept Comp Sci & Computat Valencia 46022 Spain Catholic Univ Louvain Louvain Sch Management B-1348 Louvain La Neuve Belgium

Cloud computing is being adopted by commercial and governmental organizations driven by the need to reduce the operational cost of their information technology resources and search for a scalable and flexible way to provide and release their software services. In this computing model, the Quality of Services (QoS) is agreed between service providers and their customers through Service Level Agreements (SLA). There is thus a need for systematic approaches with which to assess the quality of cloud services and their compliance with the SLA. In previous work, we introduced a generic method for Monitoring cloud Services using models at runtime (MoS@RT), which allows the monitoring requirements or the metric operationalizations of these requirements to be changed at runtime without the modification of the underlying infrastructure. In this paper, we present the design of a monitoring infrastructure that supports the proposed method with its instantiation to a specific platform and reports the results of an experiment carried out to evaluate the perceived efficacy of 58 undergraduate students when using the infrastructure to configure the monitoring of cloud services deployed on the Microsoft Azure platform. The results show that the participants perceived MoS@RT to be easy to use, useful, and they also expressed their intention to use the method in the future. Although further experiments must be carried out to strengthen these results, MoS@RT has proved to be a promising monitoring method for cloud services.

关键词： Monitoring Cloud computing Tools runtime Quality of service Measurement Service level agreements Cloud computing models@runtime quality of service (QoS) services monitoring software as a service (SaaS)

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MAsCOT: Self-adaptive Opportunistic Offloading for Cloud-Enabled Smart Mobile Applications with Probabilistic Graphical models at runtime 49

MAsCOT: Self-adaptive Opportunistic Offloading for Cloud-Ena...

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49th Hawaii International Conference on System Sciences (HICSS)

作者： Naqvi, Nayyab Zia Devlieghere, Jonas Preuveneers, Davy Berbers, Yolande Katholieke Univ Leuven iMinds DistriNet Leuven Belgium

ISBN: (纸本)9780769556703

Although extensive progress has been made in Mobile Cloud Augmentation, automated decision support on the device that enables the opportunistic and intelligent use of cloud resources is missing. Furthermore, we need solutions with reflective capabilities that can handle a changing environment and runtime variability. To simplify the deployment of smart mobile applications, we present a framework with retrospective decision support based on reinforcement learning to cater for various resource-performance trade-offs. We have adopted the MAPE-K (Monitor-Analyse-Plan-Execute-Knowledge) control loop architecture and realized the loop with Dynamic Decision Networks to manage self-adaptation at runtime. Our experiments show that our framework is capable of intelligently inferring appropriate decisions with an acceptable performance overhead of 10 milliseconds on mobile devices.

关键词： Mobile cloud computing decision support probabilistic graphical models dynamic offloading models@runtime

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Using models at runtime to Support Adaptable Monitoring of Multi-Clouds Applications 16

Using Models at Runtime to Support Adaptable Monitoring of M...

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16th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC)

作者： Cianciaruso, Lorenzo di Forenza, Francesco Di Nitto, Elisabetta Miglierina, Marco Ferry, Nicolas Solberg, Arnor Politecn Milan Dipartimento Elettron Informaz & Bioingn Politecn Milan Italy SINTEF Dept Networked Syst & Serv Oslo Norway

ISBN: (纸本)9781479984480

The ability to run and manage multi-clouds applications (i.e., applications that run on multiple clouds) allows exploiting the peculiarities of each cloud solution and hence improves non-functional aspects such as availability, cost, and scalability. Monitoring such multi-clouds applications is fundamental to track the health of the applications themselves and of their underlying infrastructures as well as to decide when and how to adapt their behaviour and deployment. It is clear that, not only the application but also the corresponding monitoring infrastructure should dynamically adapt in order to (i) be optimized to the application context (e.g., adapting the frequency of monitoring to reduce network load);(ii) to enable the co-evolution of the monitoring platform together with the cloud application (e.g., if a service migrates from one provider to another, the monitoring activities have to be adapted accordingly). In this paper, we present a model-based platform for the dynamic provisioning, deployment, and monitoring of multi-clouds applications whose monitoring activities can be automatically and dynamically adapted to best fit with the actual deployment of the application.

关键词： cloud computing adaptable multiclouds applications monitoring application context cloud application cloud solution dynamic provisioning model-based platform monitoring infrastructure nonfunctional aspects Adaptation models Cognition Computer architecture Engines Measurement Monitoring Observers adaptation cloud modaclouds models at runtime models@runtime monitoring multi-cloud multicloud Clouds Computer Architecture Engines CLOUDS Cloud Computing Cognition runtime Observers Adaptation models deployment

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MAsCOT: Self-adaptive Opportunistic Offloading for Cloud-Enabled Smart Mobile Applications with Probabilistic Graphical models at runtime

MAsCOT: Self-adaptive Opportunistic Offloading for Cloud-Ena...

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Hawaii International Conference on System Sciences

作者： Nayyab Zia Naqvi Jonas Devlieghere Davy Preuveneers Yolande Berbers iMinds-DistriNet KU Leuven

ISBN: (纸本)9781509019816

关键词： Mobile cloud computing Decision support Probabilistic graphical models Dynamic offloading models@runtime decision making support runtime Cloud Computing Mobile Applications self-adaptive Probabilistic Model Mascot Scoring Engine UNLOADING Graphical models Frameworks learning (artificial intelligence) Mobile devices

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runtime observable and adaptable UML State Machines: models@*** approach 34

Runtime observable and adaptable UML State Machines: Models@...

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34th ACM/SIGAPP Annual International Symposium on Applied Computing (SAC)

作者： Illarramendi, Miren Etxeberria, Leire Elkorobarrutia, Xabier Sagardui, Goiuria Mondragon Goi Eskola Politekn S Coop Arrasate Mondragon Spain Mondragon Goi Eskola Politekn Arrasate Mondragon Spain

ISBN: (纸本)9781450359337

An embedded system is a self-contained system that incorporates elements of control logic and real-world interaction. UML State Machines constitute a powerful formalism to model the behaviour of these types of systems. In current industrial environments, the software of these embedded systems have to cope with the increasing complexity and robustness requirements at runtime. One way to manage these requirements is having the software component's behaviour model available at runtime (models@***). Thus, it is possible to enhance the safety of the software component by enabling verification and adaptation at runtime. In this paper, we present a model-driven approach to generate software components (namely, RESCO framework), which are able both to provide their internal information in model terms at runtime and adapt their behaviour automatically when an error or an unexpected situation is detected. The aforementioned runtime introspection and adaptation abilities are added automatically to the software component and it does not require the developer make any extra effort. The solution has been tested in the design and implementation of an industrial Burner controller. Results indicate that the software components generated by the presented solution provides introspection at runtime. Thanks to this introspection ability at runtime, the software components are able to adapt automatically from their normal-mode behaviour to a safe-mode behaviour which was defined to be used in erroneous or unexpected situations at runtime. Therefore, it is possible to enhance the safety of the systems consisting of these software components.

关键词： models@runtime runtime Adaptation Embedded Systems UML State Machines

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Meta-modeling runtime models

Meta-modeling runtime models

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5th Workshop on models@run.time 2010, MRT 2010 - At the ACM/IEEE 13th International Conference on Model Driven Engineering Languages and Systems, models 2010

作者： Lehmann, Grzegorz Blumendorf, Marco Trollmann, Frank Albayrak, Sahin DAI-Labor Technische Universität Berlin Ernst-Reuter-Platz 7 10587 Berlin Germany

runtime models enable the implementation of highly adaptive applications but also require a rethinking in the way we approach models. Metamodels of runtime models must be supplemented with additional runtime concepts that have an impact on the way how runtime models are built and reflected in the underlying runtime architectures. The goal of this work is the generalization of common concepts found in different approaches utilizing runtime models and the provision of a basis for their meta-modeling. After analyzing recent works dealing with runtime models, we present a meta-modeling process for runtime models. Based on a meta-metamodel it guides the creation of metamodels combining design time and runtime concepts.

关键词： Meta-metamodel Meta-modeling models@runtime runtime models

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Online adaptation for autonomous unmanned systems driven by requirements satisfaction model

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SOFTWARE AND SYSTEMS MODELING 2022年第4期21卷 1295-1319页

作者： Luo, Yixing Zhou, Yuan Zhao, Haiyan Jin, Zhi Zhang, Tianwei Liu, Yang Barthaud, Danny Yu, Yijun Peking Univ Key Lab High Confidence Software Technol Minist Educ Beijing Peoples R China Peking Univ Sch Comp Sci Beijing Peoples R China Nanyang Technol Univ Sch Comp Sci & Engn Singapore Singapore Zhejiang Sci Tech Univ Sch Informat Sci & Technol Hangzhou Peoples R China Open Univ Sch Comp & Commun Milton Keynes Bucks England

Autonomous unmanned systems (AUSs) emerge to replace human operators for achieving better safety, efficiency, and effectiveness in harsh and difficult missions. They usually run in a highly open and dynamic operating environment, in which some unexpected situations may occur, leading to violations of predefined requirements. In order to maintain stable performance, the AUS control software needs to predict in advance whether the requirements will be violated and then make adaptations to maximize requirements satisfaction. We propose Captain, a model-driven and control-based online adaptation approach, for the AUS control software. At the modeling phase, apart from the system behavior model and the operating environment model, we construct a requirements satisfaction model. At runtime, based on the requirements satisfaction model, Captain first predicts whether the requirements will be violated in the upcoming situation;then identifies the unsatisfiable requirements that need to be accommodated;and finally, finds an optimal adaptation for the upcoming situation. We evaluate Captain in both simulated scenarios and the real world. For the former, we use two cases of UAV Delivery and UUV Ocean Surveillance, whose results demonstrate the Captain's robustness, scalability, and real-time performance. For the latter, we have successfully implemented Captain in the DJI Matrice 100 UAV with real-world workloads.

关键词： Requirements satisfaction model runtime adaptation models@runtime Autonomous unmanned systems

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EMF-Syncer: scalable maintenance of view models over heterogeneous data-centric software systems at run time

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SOFTWARE AND SYSTEMS MODELING 2023年第6期22卷 1949-1968页

作者： Boronat, Artur Univ Leicester Sch Comp & Math Sci Leicester England

With the increasing presence of cyber-physical systems (CPSs), like autonomous vehicle systems and digital twins, the future of software engineering is predicated on the importance of designing and developing data-centric software systems that can adapt intelligently at run time. CPSs consist of complex heterogeneous software components. Model-driven engineering advocates using software models to tame such complexity, capturing the relevant design concerns of such systems at different levels of abstraction. Yet most of the existing CPSs are engineered without considering MDE practices and tools, facing fundamental challenges when working with data: monitoring the program data at run time, syncing updates between program and model, dealing with heterogeneous data sources, and representing such observed data at run time to facilitate automated analysis. In this work, we introduce the notion of view models to explicitly represent parts of the domain knowledge implicitly embedded in the source code of a software system. This notion is equipped with a scalable bidirectional syncing mechanism that extracts view model instances from program snapshots at run time. The syncing mechanism is proposed from a conceptual point of view, independently of specific implementations and supports incremental view model update and view model maintenance. We show how this syncing mechanism is flexible enough to facilitate the non-intrusive adoption of MDE technology over existing MDE-agnostic heterogeneous data-centric systems. We study the run-time cost implied by the EMF-Syncer , the tool implementing this syncing mechanism for Java applications and view models atop the eclipse modeling framework (EMF) when executing data analytic and transformation tasks over large volumes of data in the presence of data updates at run time. An empirical evaluation of the EMF-Syncer has been conducted with an industry-targeted benchmark for decision support systems, analyzing performance and scalabilit

关键词： Model-driven engineering models@runtime Roundtrip synchronization View update problem

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