Adapting policy-based management of Future Networks using collaborative filtering techniques

Future Networks constitute a complex and dynamic environment which network operators are called to orchestrate uniformly and efficiently. Among others, the increase in the number and heterogeneity of network infrastructure, the complexity of devices and protocols and the explosion in traffic demands are only “few” of the issues that network operators should take into consideration. Conventional network management schemes lack in automation, harmonization and efficiency, in order to handle such chaotic environments. Autonomic network management targets the governance of the behavior of autonomic and contemporary network entities, based on network operator requirements and business goals. Policies are considered as an effective tool for accomplishing a desirable high level control. In this paper, we present a novel policy-based network management framework, while enriching its ontology-oriented inference engine with collaborative filtering capabilities thus achieving the acceleration of the decision making process.