Semantic aware processing of user defined inference rules to manage home networks

Increasing complexity makes it difficult for users to manage their home networks in a way that optimises their experience when using rich multimedia services. Current network management systems are not designed for ordinary network users-they do not seek to abstract the configuration details of network devices and services that need to be managed, requiring instead editing of configuration files with specific syntax and semantics. We investigated the use of semantic technologies to improve the ability of typical users to manage their networks by capturing their preferences using concepts familiar to them, and applying inference techniques to link monitored network events to these preferences so that appropriate configurations can be automatically applied. Our framework abstracts the detail of managing the network access and various multimedia services consumed in homes into an ontological descriptions augmented by inference rules (derived from users' interaction with system via intuitive interfaces). In this article, we specify semantic enrichment algorithms that analyse network flows concerning service usage and apply a reasoning process to identify events with user significance. These events are forwarded to a Policy Decision Point, triggering system policies that result in configuration actions. We demonstrate the power of our solution by implementing a set of use cases, and show that the semantic enrichment algorithms are flexible to suit a wide range of typical scenarios and performs better against a popular semantic search technique based on keyword interpretation.