The design of a novel context-aware policy model to support machine-based learning and reasoning

John Strassner, José Neuman de Souza, David Raymer, Srini Samudrala, Steven Davy, Keara Barrett

Research output: Contribution to journalArticlepeer-review

18 Citations (Scopus)

Abstract

The purpose of autonomic networking is to manage the business and technical complexity of networked components and systems. However, the lack of a common lingua franca makes it impossible to use vendor-specific network management data to ascertain the state of the network at any given time. Furthermore, the tools used to analyze management data are all different, and hence require different data in different formats. This complicates the construction of context from diverse information sources. This paper describes a new version of the DEN-ng context-aware policy model, which is part of the FOCALE autonomic network architecture. This model has been built using three guiding principles: (1) both the context model and the policy model are rooted in information models, so that they can govern managed entities, (2) each model is expressly constructed to facilitate the generation of ontologies, so that reasoning about policies constructed from the model may be done, and (3) the model is expressly constructed so that a policy language that supports machine-based reasoning and learning can be developed from it.

Original languageEnglish
Pages (from-to)17-43
Number of pages27
JournalCluster Computing
Volume12
Issue number1
DOIs
Publication statusPublished - 2009

Keywords

  • Autonomic architecture
  • Context
  • FOCALE
  • Machine-based learning and reasoning
  • Ontology-based management
  • Policy management
  • Semantic reasoning

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