A situatedness-based Knowledge Plane for autonomic networking

IP networks, and particularly the Internet, were proposed to be a simple and robust support for homogeneous communications. This implies that only basic control mechanisms have to be performed by network elements. Communication management has to be performed by the terminals. However, the integration of new services and the increasing need for QoS require the network to be increasingly more flexible and adaptive. New algorithms and protocols have been proposed by many research teams to address these issues, but these new algorithms tend to make network management and control more flexible. Thus, manual configuration of such flexible and adaptive network architectures is very complex, if not impossible. Self-management is then a good opportunity to address this new complexity, and then to integrate more easily new services into the network. However, this self-management requires the equipment to carry much more knowledge and information than the actual control and management planes do. Global knowledge management schemes are therefore necessary to achieve this, including new policies for knowledge gathering, computing, sharing and providing. To address this particular need for knowledge management, several studies have proposed building a new plane, called the 'Knowledge Plane' (KP). This paper studies different propositions for this KP, and presents an original vision of what this KP should be. Our vision of the KP relies on the paradigm of situatedness. This paradigm was developed by research studies in the field of multi-agent systems, which tend to solve complex problems using collaborative and autonomous agents (multi-agent technology has been largely described in Artificial Intelligence literature). These agents in our proposition are embedded within the network elements themselves. Their role is to share local and situated knowledge composing the global KP. We have also developed, as an illustration, a distributed intrusion detection system (IDS) based on the local IDS Snort. Copyright (C) 2008 John Wiley & Sons, Ltd.