Autonomic computing

L'autonomic computing ou informatique autonome est l'approche consistant à munir les logiciels et les matériels de garde-fous internes ou externes leur permettant de restaurer automatiquement leur fonction en cas d'altération non planifiée. Suscitée par la croissance et complexité des systèmes informatiques, elle a été introduite par IBM en 2001 et s'inspire fortement des recherches en agents autonomes et systèmes multi-agents. Utilité Les ordinateurs – et ce quel que soit le système d'exploitation utilisé – font intervenir des mécanismes d'une grande fragilité car les différents composants logiciels (ou matériels) s'appuient les uns sur les autres à la manière d'un château de cartes : il suffit qu'un composant (à la suite d'un incident, d'une erreur humaine ou d'une malveillance, etc.) soit altéré et c'est l'ensemble qui ne fonctionne plus correctement. Exemples d'utilisations Ainsi, sur certains serveurs IBM, une défaillance répétée d'un bit donné dans la mémoi

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Software agents are widely used to control physical, economic and financial processes. The course presents practical methods for implementing software agents and multi-agent systems, supported by programming exercises, and the theoretical underpinnings including computational game theory.

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Autonomic Resource Provisioning for Software Business Processes

Thomas Heinis

Software development nowadays involves several levels of abstraction: starting from the programming of single objects, to their combination into components, to their publication as services and the overall architecture linking elements at each level. As a result, software engineering is dealing with a wider range of artifacts and concepts (i.e., in the context of this paper: services and business processes) than ever before. In this paper we explore the importance of having an adequate engine for executing business processes written as compositions of Web services. The paper shows that, independently of the composition language used, the overall scalability of the system is determined by how the run-time engine treats the process execution. This is particularly relevant at the service level because publishing a process through a Web service interface makes it accessible to an unpredictable and potentially very large number of clients. As a consequence, the process developer is confronted with the difficult question of resource provisioning. Determining the optimal configuration of the distributed engine that runs the process becomes sensitive both to the actual number of clients and to the kinds of processes to be executed. The main contribution of the paper is to show how resource provisioning for software business processes can be solved using autonomic computing techniques. The engine separates execution in two stages (navigation and dispatching) and uses a controller to allocate the node of a cluster of computers to each one of those stages as the workload changes. The controller can be configured with different policies that define how to reconfigure the system. To prove the feasibility of the concept, we have implemented the autonomic controller and evaluated its performance with an extensive set of experiments.

2007

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An increasing amount of Web services are being implemented using process management tools and languages (BPML, BPEL, etc.). The main advantage of processes is that designers can express complex business conversations at a high level of abstraction, even reusing standardized business protocols. The downside is that the infrastructure behind the Web service becomes more complex. This is particularly critical for Web services that may be subjected to high variability in demand and suffer from unpredictable peaks of heavy load. In this paper we present a flexible architecture for process execution that has been designed to support autonomic scalability. The system runs on a cluster of computers and reacts to workload variations by altering its configuration in order to optimally use the available resources. Such changes happen automatically and without any human intervention. This feature completely removes the need for the manual monitoring and reconfiguration of the system, which in practice is a difficult and time-consuming operation. In the paper we describe the architecture of the system and present an extensive performance evaluation of its autonomic capabilities.

IEEE Computer Society2005

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JOpera: Autonomic Service Orchestration

Thomas Heinis

The increasing interest in new software engineering technologies for application integration such as Service Oriented Computing and Service Orchestration has resulted in a proliferation of workflow management systems as the underlying representation and execution platform for service composition. Workflow management system are also being applied to new domains (e.g., virtual scientific laboratories, Grid computing, service delivery and provisioning). For these new applications, workflows are seen as the modeling metaphor behind the notion of straight through processing and virtual organizations where a collection of existing heterogeneous systems are composed into an integrated solution. In all these settings workflow engines are at the core of a complex combination of applications and clustered computers. As such, they have become rather difficult to deploy and configure, let alone tune to obtain maximum performance. This problem is not unique to workflow and service composition engines but it is more difficult to address in these settings because there is only a limited understanding of the execution procedures behind a workflow engine. In this short paper we report on our ongoing work to design and develop an autonomic workflow engine that can be used for large scale service composition. The challenge we face in doing this is threefold. First, we need to design an execution procedure for service compositions that is amenable to autonomic treatment. Second, this procedure needs to be realized in an architecture that supports the deployment of different modules of the system across a computer cluster in order to achieve the desired level of performance. Third, an autonomic controller and appropriate control policies need to be developed to automatically provision the optimal amount of resources to the engine. In this paper we provide a high level description of how we have accomplished these three goals and give a brief account of the performance of the system. The implemented system is part of the JOpera project. JOpera is an advanced SOA tool for Eclipse, which provides modeling, execution, monitoring and debugging tools for workflow-based Web service orchestration.

2006

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