Integration of Knowledge Management in the MIB for the Network Management

In a heterogeneous and distributed context, the management of telecommunication networks and services is becoming increasingly important in operator and service provider environments. This management cannot be performed without the contribution of intelligent management functions, which ensure the most important management operations of provisioning, assurance and billing. More advanced tools are needed to support this activity. It is necessary to develop new models, which offer more possibilities. To resolve this difficulty in this chapter we study the integration of advanced artificial intelligence technology into existing network management models. We describe the design and implementation of a management platform using Artificial Intelligent reasoning technique. This study focuses on an intelligent framework and a language for formalizing knowledge management descriptions and combining them with existing OSI management model. In this chapter we present a methodology to specify intelligent agents, based on management OSI model. We propose a new paradigm where the intelligent network management is integrated into the conceptual repository of management information. In modern network elements management information is increasingly stored in a distributed manner locally with the network elements into Management Information Base (MIB) databases. These databases contain all relevant configuration data and the dynamic state data (measurements and alarms) in a standardized format. We study a technique which integrates the knowledge base of expert system within the MIB used to manage a network. A new property named RULE has been added in the MIB, which gathers important aspects of the facts and the knowledge base of the embedded expert system. By integrating the knowledge base in resources specifications, system has the power to provide diagnosis of fault network, which can assist engineering trainees, inspectorate staff and professional. Furthermore this paper outlines the development of an expert system prototype based in our propose GDMO+ standard and describes the most important facets, advantages and drawbacks that were found after prototyping our proposal. This paper is organized as follows. In the section immediately below, we describe the evolution of network management and the role of network management functions. We will examine the management network, including the concepts, major approaches, and management models. It starts with specific applications and work on expert systems in similar fields. We propose a new Intelligent Integrated Management Model and an extension of