A control theory foundation for self-managing computing systems

Diao, Yixin; Hellerstein, Joseph L.; Parekh, Sujay; Griffith, Rean; Kaiser, Gail E.; Phung, Dan B.

doi:10.1109/jsac.2005.857206

Cited by 89 publications

(5 citation statements)

References 17 publications

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“…From a software engineer's perspective, a controller should provide the following properties [17,25,27]:…”

Section: E Formally Evaluating the Closed Loop Systemmentioning

confidence: 99%

“…These high level objectives have counterparts in control terminology and their satisfaction can be mapped into the "by design" satisfaction of the following properties [17,66]:…”

Section: E Formally Evaluating the Closed Loop Systemmentioning

confidence: 99%

“…Pioneering works in system engineering [1,17,35] spotlighted how control theoretical results improve computing system design. These contributions have been especially influential for performance management and resource allocation; however, new trends in self-adaptive software introduce new software models and a variety of quantitative and functional requirements beyond the scope of those works.…”

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confidence: 99%

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Software Engineering Meets Control Theory

Filieri

Maggio

Angelopoulos

et al. 2015

2015 IEEE/ACM 10th International Symposium on Software Engineering for Adaptive and Self-Managing Systems

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Abstract-The software engineering community has proposed numerous approaches for making software self-adaptive. These approaches take inspiration from machine learning and control theory, constructing software that monitors and modifies its own behavior to meet goals. Control theory, in particular, has received considerable attention as it represents a general methodology for creating adaptive systems. Control-theoretical software implementations, however, tend to be ad hoc. While such solutions often work in practice, it is difficult to understand and reason about the desired properties and behavior of the resulting adaptive software and its controller.This paper discusses a control design process for software systems which enables automatic analysis and synthesis of a controller that is guaranteed to have the desired properties and behavior. The paper documents the process and illustrates its use in an example that walks through all necessary steps for self-adaptive controller synthesis.

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“…From a software engineer's perspective, a controller should provide the following properties [17,25,27]:…”

Section: E Formally Evaluating the Closed Loop Systemmentioning

confidence: 99%

“…These high level objectives have counterparts in control terminology and their satisfaction can be mapped into the "by design" satisfaction of the following properties [17,66]:…”

Section: E Formally Evaluating the Closed Loop Systemmentioning

confidence: 99%

mentioning

confidence: 99%

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Software Engineering Meets Control Theory

Filieri

Maggio

Angelopoulos

et al. 2015

2015 IEEE/ACM 10th International Symposium on Software Engineering for Adaptive and Self-Managing Systems

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“…Deepening the analysis, one may object that many works deal with computing system control, and do use control-theoretical methodologies, see, for example, [8][9][10][11] and, particularly, [12]. This is true, but virtually all of them take the computing system as is and close loops around it (e.g., aiming at a certain Central Processing Unit (CPU) distribution by altering task deadlines).…”

Section: The Quest For Physicsmentioning

confidence: 99%

A dynamic modelling framework for control-based computing system design

Papadopoulos

Maggio

Terraneo

et al. 2014

Mathematical and Computer Modelling of Dynamical Systems

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This manuscript proposes a novel viewpoint on computing systems' modelling. The classical approach is to consider fully functional systems and model them, aiming at closing some external loops to optimize their behaviour. On the contrary, we only model strictly physical phenomena, and realize the rest of the system as a set of controllers. Such an approach permits rigorous assessment of the obtained behaviour in mathematical terms, which is hardly possible with the heuristic design techniques, that were mainly adopted to date. The proposed approach is shown at work with three relevant case studies, so that a significant generality can be inferred from it.

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“…Control Theory models include the classical feed-back or reactive control, on which the current state is observed to detect deviations with respect to a target state, and also predictive control, on which a model of the system is used to predict the future behavior over a prediction horizon [1]. Developing a controller for a system requires the mapping of the particular QoS control problem into a system of feedback loops, developing effective resource models, choosing proper actuators, handling sensor delays, and addressing lead times in effector's actions [72] [2].…”

Section: Approachesmentioning

confidence: 99%

A Middleware framework for self-adaptive large scale distributed services

Martı́nez¹

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Modern service-oriented applications demand the ability to adapt to changing conditions and unexpected situations while maintaining a required QoS. Existing self-adaptation approaches seem inadequate to address this challenge because many of their assumptions are not met on the large-scale, highly dynamic infrastructures where these applications are generally deployed on. The main motivation of our research is to devise principles that guide the construction of large scale self-adaptive distributed services. We aim to provide sound modeling abstractions based on a clear conceptual background, and their realization as a middleware framework that supports the development of such services. Taking the inspiration from the concepts of decentralized markets in economics, we propose a solution based on three principles: emergent self-organization, utility driven behavior and model-less adaptation. Based on these principles, we designed Collectives, a middleware framework which provides a comprehensive solution for the diverse adaptation concerns that rise in the development of distributed systems. We tested the soundness and comprehensiveness of the Collectives framework by implementing eUDON, a middleware for self-adaptive web services, which we then evaluated extensively by means of a simulation model to analyze its adaptation capabilities in diverse settings. We found that eUDON exhibits the intended properties: it adapts to diverse conditions like peaks in the workload and massive failures, maintaining its QoS and using efficiently the available resources; it is highly scalable and robust; can be implemented on existing services in a non-intrusive way; and do not require any performance model of the services, their workload or the resources they use. We can conclude that our work proposes a solution for the requirements of self-adaptation in demanding usage scenarios without introducing additional complexity. In that sense, we believe we make a significant contribution towards the development of future generation service-oriented applications. Las Aplicaciones Orientadas a Servicios modernas demandan la capacidad de adaptarse a condiciones variables y situaciones inesperadas mientras mantienen un cierto nivel de servio esperado (QoS). Los enfoques de auto-adaptación existentes parecen no ser adacuados debido a sus supuestos no se cumplen en infrastructuras compartidas de gran escala. La principal motivación de nuestra investigación es inerir un conjunto de principios para guiar el desarrollo de servicios auto-adaptativos de gran escala. Nuesto objetivo es proveer abstraciones de modelaje apropiadas, basadas en un marco conceptual claro, y su implemetnacion en un middleware que soporte el desarrollo de estos servicios. Tomando como inspiración conceptos económicos de mercados decentralizados, hemos propuesto una solución basada en tres principios: auto-organización emergente, comportamiento guiado por la utilidad y adaptación sin modelos. Basados en estos principios diseñamos Collectives, un middleware que proveer una solución exhaustiva para los diversos aspectos de adaptación que surgen en el desarrollo de sistemas distribuidos. La adecuación y completitud de Collectives ha sido provada por medio de la implementación de eUDON, un middleware para servicios auto-adaptativos, el ha sido evaluado de manera exhaustiva por medio de un modelo de simulación, analizando sus propiedades de adaptación en diversos escenarios de uso. Hemos encontrado que eUDON exhibe las propiedades esperadas: se adapta a diversas condiciones como picos en la carga de trabajo o fallos masivos, mateniendo su calidad de servicio y haciendo un uso eficiente de los recusos disponibles. Es altamente escalable y robusto; puedeoo ser implementado en servicios existentes de manera no intrusiva; y no requiere la obtención de un modelo de desempeño para los servicios. Podemos concluir que nuestro trabajo nos ha permitido desarrollar una solucion que aborda los requerimientos de auto-adaptacion en escenarios de uso exigentes sin introducir complejidad adicional. En este sentido, consideramos que nuestra propuesta hace una contribución significativa hacia el desarrollo de la futura generación de aplicaciones orientadas a servicios.

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A control theory foundation for self-managing computing systems

Cited by 89 publications

References 17 publications

Software Engineering Meets Control Theory

Software Engineering Meets Control Theory

A dynamic modelling framework for control-based computing system design

A Middleware framework for self-adaptive large scale distributed services

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