Autonomic policy-based HAN traffic classification using augmented meta model for policy translation

Translating between network management policies is desirable if a system needs to map downwards from a high-level objective to low-level configurations or to feed information back upwards from a network event to a matching policy. Techniques for policy translation require elements of semantic mapping between levels of management policy within a continuum. The policy translation is difficult due to the inherent complexity of transforming abstract policy concepts into the concrete policies. Formal semantic models can harness this translation process but existing policy languages do not provide semantic models that capture concepts embodied in policy languages. In this article, we attempt to explain how to refine user-level policies using SWRL rules into network-level policies using IPTables with the help of a simplified policy framework in the domain of home area network. We also present the testbed architecture used for experiments in home area network environment for traffic classification. The main contribution of this article is the extension of semantic translation algorithm, which is used to map policy concepts in policy languages to meta-model concepts. Finally, we compare different semantic mapping techniques with our proposed technique.