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- W1916248610 abstract "Cloud computing has grown rapidly during the past fewyears and has become a fundamental paradigm in the InformationTechnology (IT) area. Clouds enable dynamic, scalableand rapid provision of services through a computer network,usually the Internet. However, managing and optimisingclouds and their services in the presence of dynamism andheterogeneity is one of the major challenges faced by industryand academia. A prominent solution is resorting to selfmanagementas fostered by autonomic computing.Self-management requires knowledge about the system andthe environment to enact the self-* properties. Nevertheless,the characteristics of cloud, such as large-scale and dynamism,hinder the knowledge discovery process. Moreover, cloud systemsabstract the complexity of the infrastructure underlyingthe provided services to their customers, which obfuscatesseveral details of the provided services and, thus, obstructsthe effectiveness of autonomic managers.While a large body of work has been devoted to decisionmakingand autonomic management in the cloud domain,there is still a lack of adequate solutions for the provision ofknowledge to these processes.In view of the lack of comprehensive solutions for the provisionof knowledge to the autonomic management of clouds,we propose a theoretical and practical framework which addressesthree major aspects of this process: (i) the definitionof services’ provision through the specification of a formallanguage to define Service-Level-Agreements for the cloud domain;(ii) the collection and processing of information throughan extensible knowledge discovery architecture to monitorautonomic clouds with support to the knowledge discoveryprocess; and (iii) the knowledge discovery through a machinelearning methodology to calculate the similarity among services,which can be employed for different purposes, e.g. servicescheduling and anomalous behaviour detection. Finally,in a case study, we integrate the proposed solutions and showthe benefits of this integration in a hybrid cloud test-bed." @default.
- W1916248610 created "2016-06-24" @default.
- W1916248610 creator A5070595259 @default.
- W1916248610 date "2015-03-01" @default.
- W1916248610 modified "2023-10-03" @default.
- W1916248610 title "Supporting Autonomic Management of Clouds:Service-Level-Agreement, Cloud Monitoringand Similarity Learning" @default.
- W1916248610 hasPublicationYear "2015" @default.
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