A Component Platform for Experimenting with Autonomic Composition

International audienceIn this paper, we propose a component-oriented framework that can support autonomic computing and in particular bio-inspired approaches. Starting from the Grid Component Model, a component model targeting at Grid computing and already featuring some autonomicity, we show how such a model can be used in a general autonomic computing context. Indeed the model provides hierarchical structure and reconfiguration for both functional and non-functional levels. This should ease the development of \textit{self-*} and in particular, self-evolving applications. With our approach, even the autonomic strategies themselves can evolve. We consider this model and its implementation as powerful tools for easily experimenting autonomic behaviours

A Middleware Framework for Constraint-Based Deployment and Autonomic Management of Distributed Applications

We propose a middleware framework for deployment and subsequent autonomic management of component-based distributed applications. An initial deployment goal is specified using a declarative constraint language, expressing constraints over aspects such as component-host mappings and component interconnection topology. A constraint solver is used to find a configuration that satisfies the goal, and the configuration is deployed automatically. The deployed application is instrumented to allow subsequent autonomic management. If, during execution, the manager detects that the original goal is no longer being met, the satisfy/deploy process can be repeated automatically in order to generate a revised deployment that does meet the goal.Comment: Submitted to Middleware 0

mRUBiS: An Exemplar for Model-Based Architectural Self-Healing and Self-Optimization

Self-adaptive software systems are often structured into an adaptation engine that manages an adaptable software by operating on a runtime model that represents the architecture of the software (model-based architectural self-adaptation). Despite the popularity of such approaches, existing exemplars provide application programming interfaces but no runtime model to develop adaptation engines. Consequently, there does not exist any exemplar that supports developing, evaluating, and comparing model-based self-adaptation off the shelf. Therefore, we present mRUBiS, an extensible exemplar for model-based architectural self-healing and self-optimization. mRUBiS simulates the adaptable software and therefore provides and maintains an architectural runtime model of the software, which can be directly used by adaptation engines to realize and perform self-adaptation. Particularly, mRUBiS supports injecting issues into the model, which should be handled by self-adaptation, and validating the model to assess the self-adaptation. Finally, mRUBiS allows developers to explore variants of adaptation engines (e.g., event-driven self-adaptation) and to evaluate the effectiveness, efficiency, and scalability of the engines

Self-Configuration and Self-Optimization Autonomic Skeletons using Events

International audienceThis paper presents a novel way to introduce self-configuration and self-optimization autonomic characteristics to algorithmic skeletons using event driven programming techniques. Based on an algorithmic skeleton language, we show that the use of events greatly improves the estimation of the remaining computation time for skeleton execution. Events allow us to precisely monitor the status of the execution of algorithmic skeletons. Using such events, we provide a framework for the execution of skeletons with a very high level of adaptability. We focus mainly on guaranteeing a given execution time for a skeleton, by optimizing autonomically the number of threads allocated. The proposed solution is independent from the platform chosen for executing the skeleton for example we illustrate our approach in a multicore setting, but it could also be adapted to a distributed execution environment

07061 Abstracts Collection -- Autonomous and Adaptive Web Services

From 4.2.2007 to 9.2.2007, the Dagstuhl Seminar 07061 ``Autonomous and Adaptive Web Services\u27\u27 was held in the International Conference and Research Center (IBFI), Schloss Dagstuhl. During the seminar, several participants presented their current research, and ongoing work and open problems were discussed. Abstracts of the presentations given during the seminar as well as abstracts of seminar results and ideas are put together in this paper. The first section describes the seminar topics and goals in general. Links to extended abstracts or full papers are provided, if available

Losing control:the case for emergent software systems using autonomous assembly, perception and learning

Architectural self-organisation, in which different configurations of software modules are dynamically assembled based on the current context, has been shown to be an effective way for software to self-optimise over time. Current approaches to this rely heavily on human-led definitions: models, policies and processes to control how self-organisation works. We present the case for a paradigm shift to fully emergent computer software which places the burden of understanding entirely into the hands of software itself. These systems are autonomously assembled at runtime from discovered constituent parts and their internal health and external deployment environment continually monitored. An online, unsupervised learning system then uses runtime adaptation to explore alternative system assemblies and locate optimal solutions. Based on our experience to date, we define the problem space of emergent software, and we present a working case study of an emergent web server. Our results demonstrate two aspects of the problem space for this case study: that different assemblies of behaviour are optimal in different deployment environment conditions; and that these assemblies can be autonomously learned from generalised perception data while the system is online

Intention-oriented programming support for runtime adaptive autonomic cloud-based applications

The continuing high rate of advances in information and communication systems technology creates many new commercial opportunities but also engenders a range of new technical challenges around maximising systems' dependability, availability, adaptability, and auditability. These challenges are under active research, with notable progress made in the support for dependable software design and management. Runtime support, however, is still in its infancy and requires further research. This paper focuses on a requirements model for the runtime execution and control of an intention-oriented Cloud-Based Application. Thus, a novel requirements modelling process referred to as Provision, Assurance and Auditing, and an associated framework are defined and developed where a given system's non/functional requirements are modelled in terms of intentions and encoded in a standard open mark-up language. An autonomic intention-oriented programming model, using the Neptune language, then handles its deployment and execution. © 2013 Elsevier Ltd. All rights reserved

An Approach to Autonomizing Legacy Systems

Adding adaptation capabilities to existing distributed systems is a major concern. The question addressed here is how to retrofit existing systems with self-healing, adaptation and/or self management capabilities. The problem is obviously intensified for 'systems of systems' composed of components, whether new or legacy, that may have been developed by different vendors, mixing and matching COTS and 'open source' components. This system composition model is expected to be increasingly common in high performance computing. The usual approach is to train technicians to understand the complexities of these components and their connections, including performance tuning parameters, so that they can then manually monitor and reconfigure the system as needed. We envision instead attaching a 'standard' feedback loop infrastructure to existing distributed systems for the purposes of continual monitoring and dynamically adapting their activities and performance. (This approach can also be applied to 'new' systems, as an alternative to 'building in' adaptation facilities, but we do not address that here.) Our proposed infrastructure consists of multiple layers with the objectives of probing, measuring and reporting of activity and state within the execution of the legacy system among its components and connectors; gauging, analysis and interpretation of the reported events; and possible feedback to focus the probes and gauges to drill deeper, or when necessary - direct but automatic reconfiguration of the running system